Overview

Dataset statistics

Number of variables62
Number of observations60
Missing cells1445
Missing cells (%)38.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory29.2 KiB
Average record size in memory498.1 B

Variable types

Numeric13
Categorical40
Unsupported9

Alerts

airdate has constant value "2020-12-13" Constant
_embedded.show.dvdCountry.name has constant value "Ukraine" Constant
_embedded.show.dvdCountry.code has constant value "UA" Constant
_embedded.show.dvdCountry.timezone has constant value "Europe/Zaporozhye" Constant
url has a high cardinality: 60 distinct values High cardinality
name has a high cardinality: 57 distinct values High cardinality
_links.self.href has a high cardinality: 60 distinct values High cardinality
id is highly correlated with rating.average and 1 other fieldsHigh correlation
season is highly correlated with _embedded.show.id and 3 other fieldsHigh correlation
number is highly correlated with rating.average and 1 other fieldsHigh correlation
runtime is highly correlated with rating.average and 4 other fieldsHigh correlation
rating.average is highly correlated with id and 8 other fieldsHigh correlation
_embedded.show.id is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with id and 6 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.averageHigh correlation
_embedded.show.network.id is highly correlated with season and 6 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
id is highly correlated with rating.average and 1 other fieldsHigh correlation
season is highly correlated with number and 2 other fieldsHigh correlation
number is highly correlated with season and 1 other fieldsHigh correlation
runtime is highly correlated with season and 3 other fieldsHigh correlation
rating.average is highly correlated with id and 8 other fieldsHigh correlation
_embedded.show.id is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with season and 2 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with id and 4 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with _embedded.show.id and 3 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.averageHigh correlation
_embedded.show.webChannel.id is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
id is highly correlated with rating.average and 1 other fieldsHigh correlation
season is highly correlated with _embedded.show.id and 3 other fieldsHigh correlation
number is highly correlated with rating.average and 1 other fieldsHigh correlation
runtime is highly correlated with rating.average and 2 other fieldsHigh correlation
rating.average is highly correlated with id and 8 other fieldsHigh correlation
_embedded.show.id is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with id and 4 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.averageHigh correlation
_embedded.show.network.id is highly correlated with season and 5 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.averageHigh correlation
_embedded.show.webChannel.id is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
id is highly correlated with url and 39 other fieldsHigh correlation
url is highly correlated with id and 45 other fieldsHigh correlation
name is highly correlated with id and 40 other fieldsHigh correlation
season is highly correlated with id and 25 other fieldsHigh correlation
number is highly correlated with id and 32 other fieldsHigh correlation
type is highly correlated with url and 29 other fieldsHigh correlation
airtime is highly correlated with id and 34 other fieldsHigh correlation
airstamp is highly correlated with id and 42 other fieldsHigh correlation
runtime is highly correlated with id and 36 other fieldsHigh correlation
summary is highly correlated with id and 40 other fieldsHigh correlation
image.medium is highly correlated with id and 42 other fieldsHigh correlation
image.original is highly correlated with id and 42 other fieldsHigh correlation
_links.self.href is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 39 other fieldsHigh correlation
_embedded.show.url is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.name is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.type is highly correlated with url and 43 other fieldsHigh correlation
_embedded.show.language is highly correlated with url and 38 other fieldsHigh correlation
_embedded.show.status is highly correlated with url and 31 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.premiered is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.ended is highly correlated with id and 32 other fieldsHigh correlation
_embedded.show.officialSite is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.schedule.time is highly correlated with url and 33 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with id and 33 other fieldsHigh correlation
_embedded.show.weight is highly correlated with id and 39 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 32 other fieldsHigh correlation
_embedded.show.network.name is highly correlated with id and 40 other fieldsHigh correlation
_embedded.show.network.country.name is highly correlated with id and 40 other fieldsHigh correlation
_embedded.show.network.country.code is highly correlated with id and 40 other fieldsHigh correlation
_embedded.show.network.country.timezone is highly correlated with id and 40 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.externals.imdb is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.image.medium is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.image.original is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.summary is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.updated is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show._links.self.href is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show._links.previousepisode.href is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with id and 39 other fieldsHigh correlation
_embedded.show.webChannel.name is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.webChannel.officialSite is highly correlated with url and 31 other fieldsHigh correlation
_embedded.show.webChannel.country.name is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.webChannel.country.code is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.webChannel.country.timezone is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show._links.nextepisode.href is highly correlated with id and 32 other fieldsHigh correlation
number has 4 (6.7%) missing values Missing
runtime has 6 (10.0%) missing values Missing
summary has 44 (73.3%) missing values Missing
rating.average has 58 (96.7%) missing values Missing
image.medium has 35 (58.3%) missing values Missing
image.original has 35 (58.3%) missing values Missing
_embedded.show.runtime has 19 (31.7%) missing values Missing
_embedded.show.averageRuntime has 4 (6.7%) missing values Missing
_embedded.show.ended has 39 (65.0%) missing values Missing
_embedded.show.officialSite has 2 (3.3%) missing values Missing
_embedded.show.rating.average has 54 (90.0%) missing values Missing
_embedded.show.network.id has 53 (88.3%) missing values Missing
_embedded.show.network.name has 53 (88.3%) missing values Missing
_embedded.show.network.country.name has 53 (88.3%) missing values Missing
_embedded.show.network.country.code has 53 (88.3%) missing values Missing
_embedded.show.network.country.timezone has 53 (88.3%) missing values Missing
_embedded.show.network.officialSite has 58 (96.7%) missing values Missing
_embedded.show.webChannel has 60 (100.0%) missing values Missing
_embedded.show.dvdCountry has 60 (100.0%) missing values Missing
_embedded.show.externals.tvrage has 60 (100.0%) missing values Missing
_embedded.show.externals.thetvdb has 17 (28.3%) missing values Missing
_embedded.show.externals.imdb has 29 (48.3%) missing values Missing
_embedded.show.image.medium has 4 (6.7%) missing values Missing
_embedded.show.image.original has 4 (6.7%) missing values Missing
_embedded.show.summary has 5 (8.3%) missing values Missing
image has 60 (100.0%) missing values Missing
_embedded.show.network has 60 (100.0%) missing values Missing
_embedded.show.webChannel.id has 3 (5.0%) missing values Missing
_embedded.show.webChannel.name has 3 (5.0%) missing values Missing
_embedded.show.webChannel.country has 60 (100.0%) missing values Missing
_embedded.show.webChannel.officialSite has 39 (65.0%) missing values Missing
_embedded.show.webChannel.country.name has 22 (36.7%) missing values Missing
_embedded.show.webChannel.country.code has 22 (36.7%) missing values Missing
_embedded.show.webChannel.country.timezone has 22 (36.7%) missing values Missing
_embedded.show._links.nextepisode.href has 55 (91.7%) missing values Missing
_embedded.show.image has 60 (100.0%) missing values Missing
_embedded.show.dvdCountry.name has 59 (98.3%) missing values Missing
_embedded.show.dvdCountry.code has 59 (98.3%) missing values Missing
_embedded.show.dvdCountry.timezone has 59 (98.3%) missing values Missing
url is uniformly distributed Uniform
name is uniformly distributed Uniform
summary is uniformly distributed Uniform
rating.average is uniformly distributed Uniform
image.medium is uniformly distributed Uniform
image.original is uniformly distributed Uniform
_links.self.href is uniformly distributed Uniform
_embedded.show.network.name is uniformly distributed Uniform
_embedded.show.network.country.name is uniformly distributed Uniform
_embedded.show.network.country.code is uniformly distributed Uniform
_embedded.show.network.country.timezone is uniformly distributed Uniform
_embedded.show.network.officialSite is uniformly distributed Uniform
_embedded.show._links.nextepisode.href is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
_links.self.href has unique values Unique
_embedded.show.genres is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.schedule.days is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.dvdCountry is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.externals.tvrage is an unsupported type, check if it needs cleaning or further analysis Unsupported
image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel.country is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.image is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2022-09-06 02:42:06.221654
Analysis finished2022-09-06 02:42:22.559448
Duration16.34 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2044621.35
Minimum1956339
Maximum2318103
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size608.0 B
2022-09-05T21:42:22.627144image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1956339
5-th percentile1965850.15
Q11984031.25
median1998362.5
Q32071475.25
95-th percentile2256550.6
Maximum2318103
Range361764
Interquartile range (IQR)87444

Descriptive statistics

Standard deviation91960.28183
Coefficient of variation (CV)0.04497668081
Kurtosis1.109236495
Mean2044621.35
Median Absolute Deviation (MAD)25431.5
Skewness1.423134419
Sum122677281
Variance8456693434
MonotonicityNot monotonic
2022-09-05T21:42:22.742147image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21212681
 
1.7%
19850461
 
1.7%
21117051
 
1.7%
19851151
 
1.7%
19644471
 
1.7%
20372791
 
1.7%
19850931
 
1.7%
19830441
 
1.7%
19968161
 
1.7%
19972991
 
1.7%
Other values (50)50
83.3%
ValueCountFrequency (%)
19563391
1.7%
19626741
1.7%
19644471
1.7%
19659241
1.7%
19677561
1.7%
19692281
1.7%
19740511
1.7%
19757441
1.7%
19772501
1.7%
19773211
1.7%
ValueCountFrequency (%)
23181031
1.7%
22747071
1.7%
22673161
1.7%
22559841
1.7%
22346891
1.7%
21956011
1.7%
21785621
1.7%
21761301
1.7%
21659301
1.7%
21260351
1.7%

url
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size608.0 B
https://www.tvmaze.com/episodes/2121268/fiksiki-4x17-internet-magazin
 
1
https://www.tvmaze.com/episodes/1985046/a-seba-znau-1x12-12-vypusk-garik-harlamov
 
1
https://www.tvmaze.com/episodes/2111705/world-wonder-ring-stardom-2020-12-13-stardom-road-to-osaka-dream-cinderella-tag-1
 
1
https://www.tvmaze.com/episodes/1985115/redakcia-s03-special-redakcia-news-novogodnij-lokdaun-castnaa-zizn-silovikov-obokrali-specbort
 
1
https://www.tvmaze.com/episodes/1964447/bani-negri-pentru-zile-albe-1x04-ascunzatoarea
 
1
Other values (55)
55 

Length

Max length151
Median length97
Mean length84.31666667
Min length62

Characters and Unicode

Total characters5059
Distinct characters39
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/2121268/fiksiki-4x17-internet-magazin
2nd rowhttps://www.tvmaze.com/episodes/1985046/a-seba-znau-1x12-12-vypusk-garik-harlamov
3rd rowhttps://www.tvmaze.com/episodes/1956339/hero-return-1x10-episode-10
4th rowhttps://www.tvmaze.com/episodes/1985601/swallowed-star-1x04-episode-4
5th rowhttps://www.tvmaze.com/episodes/2052508/wu-shen-zhu-zai-1x83-episode-83

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/2121268/fiksiki-4x17-internet-magazin1
 
1.7%
https://www.tvmaze.com/episodes/1985046/a-seba-znau-1x12-12-vypusk-garik-harlamov1
 
1.7%
https://www.tvmaze.com/episodes/2111705/world-wonder-ring-stardom-2020-12-13-stardom-road-to-osaka-dream-cinderella-tag-11
 
1.7%
https://www.tvmaze.com/episodes/1985115/redakcia-s03-special-redakcia-news-novogodnij-lokdaun-castnaa-zizn-silovikov-obokrali-specbort1
 
1.7%
https://www.tvmaze.com/episodes/1964447/bani-negri-pentru-zile-albe-1x04-ascunzatoarea1
 
1.7%
https://www.tvmaze.com/episodes/2037279/veneno-s01-special-mas-de-veneno-el-documental1
 
1.7%
https://www.tvmaze.com/episodes/1985093/cuzie-pisma-1x21-otnosenia-i-byt-lubov-posle-50-on-brosil-mena-vo-sne1
 
1.7%
https://www.tvmaze.com/episodes/1983044/ultra-galaxy-fight-the-absolute-conspiracy-1x04-part-41
 
1.7%
https://www.tvmaze.com/episodes/1996816/pappas-pojkar-1x04-leos-triangeldrama-med-en-golddigger1
 
1.7%
https://www.tvmaze.com/episodes/1997299/the-george-lucas-talk-show-1x19-episode-xix-investors-meeting1
 
1.7%
Other values (50)50
83.3%

Length

2022-09-05T21:42:22.857102image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/2121268/fiksiki-4x17-internet-magazin1
 
1.7%
https://www.tvmaze.com/episodes/1985046/a-seba-znau-1x12-12-vypusk-garik-harlamov1
 
1.7%
https://www.tvmaze.com/episodes/1977321/stjernestov-1x13-episode-131
 
1.7%
https://www.tvmaze.com/episodes/1956339/hero-return-1x10-episode-101
 
1.7%
https://www.tvmaze.com/episodes/1985601/swallowed-star-1x04-episode-41
 
1.7%
https://www.tvmaze.com/episodes/2052508/wu-shen-zhu-zai-1x83-episode-831
 
1.7%
https://www.tvmaze.com/episodes/1965924/new-japan-pro-wrestling-2020-12-13-super-j-cup-20201
 
1.7%
https://www.tvmaze.com/episodes/2012321/mans-diary-2x06-episode-61
 
1.7%
https://www.tvmaze.com/episodes/2071471/youths-in-the-breeze-1x01-the-boy-and-the-cat-011
 
1.7%
https://www.tvmaze.com/episodes/2071472/youths-in-the-breeze-1x02-the-boy-and-the-cat-021
 
1.7%
Other values (50)50
83.3%

Most occurring characters

ValueCountFrequency (%)
e422
 
8.3%
-414
 
8.2%
s321
 
6.3%
t309
 
6.1%
/300
 
5.9%
o269
 
5.3%
a237
 
4.7%
w199
 
3.9%
i181
 
3.6%
p174
 
3.4%
Other values (29)2233
44.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3472
68.6%
Decimal Number693
 
13.7%
Other Punctuation480
 
9.5%
Dash Punctuation414
 
8.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e422
12.2%
s321
 
9.2%
t309
 
8.9%
o269
 
7.7%
a237
 
6.8%
w199
 
5.7%
i181
 
5.2%
p174
 
5.0%
m170
 
4.9%
d136
 
3.9%
Other values (15)1054
30.4%
Decimal Number
ValueCountFrequency (%)
1155
22.4%
0103
14.9%
295
13.7%
961
 
8.8%
353
 
7.6%
551
 
7.4%
449
 
7.1%
749
 
7.1%
643
 
6.2%
834
 
4.9%
Other Punctuation
ValueCountFrequency (%)
/300
62.5%
.120
 
25.0%
:60
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-414
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3472
68.6%
Common1587
31.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e422
12.2%
s321
 
9.2%
t309
 
8.9%
o269
 
7.7%
a237
 
6.8%
w199
 
5.7%
i181
 
5.2%
p174
 
5.0%
m170
 
4.9%
d136
 
3.9%
Other values (15)1054
30.4%
Common
ValueCountFrequency (%)
-414
26.1%
/300
18.9%
1155
 
9.8%
.120
 
7.6%
0103
 
6.5%
295
 
6.0%
961
 
3.8%
:60
 
3.8%
353
 
3.3%
551
 
3.2%
Other values (4)175
11.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII5059
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e422
 
8.3%
-414
 
8.2%
s321
 
6.3%
t309
 
6.1%
/300
 
5.9%
o269
 
5.3%
a237
 
4.7%
w199
 
3.9%
i181
 
3.6%
p174
 
3.4%
Other values (29)2233
44.1%

name
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM

Distinct57
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size608.0 B
Episode 4
 
2
Episode 6
 
2
Episode 3
 
2
Интернет-магазин
 
1
Episode 21
 
1
Other values (52)
52 

Length

Max length100
Median length61
Mean length22.3
Min length5

Characters and Unicode

Total characters1338
Distinct characters119
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)90.0%

Sample

1st rowИнтернет-магазин
2nd row12 выпуск – Гарик Харламов
3rd rowEpisode 10
4th rowEpisode 4
5th rowEpisode 83

Common Values

ValueCountFrequency (%)
Episode 42
 
3.3%
Episode 62
 
3.3%
Episode 32
 
3.3%
Интернет-магазин1
 
1.7%
Episode 211
 
1.7%
Редакция. News: новогодний локдаун, частная жизнь силовиков, обокрали спецборт1
 
1.7%
Ascunzătoarea1
 
1.7%
Más de Veneno: El documental1
 
1.7%
"Отношения и быт", "Любовь после 50", "Он бросил меня во сне"1
 
1.7%
Part 41
 
1.7%
Other values (47)47
78.3%

Length

2022-09-05T21:42:22.964930image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode16
 
6.8%
the15
 
6.4%
and7
 
3.0%
boy6
 
2.5%
cat6
 
2.5%
44
 
1.7%
13
 
1.3%
el2
 
0.8%
york2
 
0.8%
new2
 
0.8%
Other values (166)173
73.3%

Most occurring characters

ValueCountFrequency (%)
176
 
13.2%
e76
 
5.7%
o59
 
4.4%
a56
 
4.2%
s48
 
3.6%
r45
 
3.4%
i42
 
3.1%
d40
 
3.0%
n38
 
2.8%
E32
 
2.4%
Other values (109)726
54.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter820
61.3%
Uppercase Letter218
 
16.3%
Space Separator176
 
13.2%
Decimal Number72
 
5.4%
Other Punctuation43
 
3.2%
Dash Punctuation4
 
0.3%
Close Punctuation2
 
0.1%
Currency Symbol2
 
0.1%
Open Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e76
 
9.3%
o59
 
7.2%
a56
 
6.8%
s48
 
5.9%
r45
 
5.5%
i42
 
5.1%
d40
 
4.9%
n38
 
4.6%
l29
 
3.5%
t29
 
3.5%
Other values (47)358
43.7%
Uppercase Letter
ValueCountFrequency (%)
E32
14.7%
T27
12.4%
H16
 
7.3%
A16
 
7.3%
C15
 
6.9%
N12
 
5.5%
S11
 
5.0%
D10
 
4.6%
B9
 
4.1%
Y9
 
4.1%
Other values (26)61
28.0%
Decimal Number
ValueCountFrequency (%)
017
23.6%
214
19.4%
113
18.1%
46
 
8.3%
56
 
8.3%
36
 
8.3%
65
 
6.9%
73
 
4.2%
91
 
1.4%
81
 
1.4%
Other Punctuation
ValueCountFrequency (%)
,12
27.9%
#9
20.9%
"8
18.6%
:7
16.3%
'2
 
4.7%
/2
 
4.7%
.1
 
2.3%
?1
 
2.3%
@1
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
-3
75.0%
1
 
25.0%
Currency Symbol
ValueCountFrequency (%)
$1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
176
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin806
60.2%
Common300
 
22.4%
Cyrillic232
 
17.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e76
 
9.4%
o59
 
7.3%
a56
 
6.9%
s48
 
6.0%
r45
 
5.6%
i42
 
5.2%
d40
 
5.0%
n38
 
4.7%
E32
 
4.0%
l29
 
3.6%
Other values (43)341
42.3%
Cyrillic
ValueCountFrequency (%)
о26
 
11.2%
и18
 
7.8%
н17
 
7.3%
а16
 
6.9%
е14
 
6.0%
с13
 
5.6%
л12
 
5.2%
р12
 
5.2%
к11
 
4.7%
м10
 
4.3%
Other values (30)83
35.8%
Common
ValueCountFrequency (%)
176
58.7%
017
 
5.7%
214
 
4.7%
113
 
4.3%
,12
 
4.0%
#9
 
3.0%
"8
 
2.7%
:7
 
2.3%
46
 
2.0%
56
 
2.0%
Other values (16)32
 
10.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII1097
82.0%
Cyrillic232
 
17.3%
None7
 
0.5%
Currency Symbols1
 
0.1%
Punctuation1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
176
 
16.0%
e76
 
6.9%
o59
 
5.4%
a56
 
5.1%
s48
 
4.4%
r45
 
4.1%
i42
 
3.8%
d40
 
3.6%
n38
 
3.5%
E32
 
2.9%
Other values (61)485
44.2%
Cyrillic
ValueCountFrequency (%)
о26
 
11.2%
и18
 
7.8%
н17
 
7.3%
а16
 
6.9%
е14
 
6.0%
с13
 
5.6%
л12
 
5.2%
р12
 
5.2%
к11
 
4.7%
м10
 
4.3%
Other values (30)83
35.8%
None
ValueCountFrequency (%)
ė2
28.6%
é1
14.3%
ø1
14.3%
ă1
14.3%
á1
14.3%
É1
14.3%
Currency Symbols
ValueCountFrequency (%)
1
100.0%
Punctuation
ValueCountFrequency (%)
1
100.0%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct8
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean136.95
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size608.0 B
2022-09-05T21:42:23.047431image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32.25
95-th percentile2020
Maximum2020
Range2019
Interquartile range (IQR)1.25

Descriptive statistics

Standard deviation507.5498615
Coefficient of variation (CV)3.706096104
Kurtosis11.06706204
Mean136.95
Median Absolute Deviation (MAD)0
Skewness3.563250106
Sum8217
Variance257606.8619
MonotonicityNot monotonic
2022-09-05T21:42:23.124308image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
139
65.0%
26
 
10.0%
36
 
10.0%
20204
 
6.7%
52
 
3.3%
41
 
1.7%
61
 
1.7%
481
 
1.7%
ValueCountFrequency (%)
139
65.0%
26
 
10.0%
36
 
10.0%
41
 
1.7%
52
 
3.3%
61
 
1.7%
481
 
1.7%
20204
 
6.7%
ValueCountFrequency (%)
20204
 
6.7%
481
 
1.7%
61
 
1.7%
52
 
3.3%
41
 
1.7%
36
 
10.0%
26
 
10.0%
139
65.0%

number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct25
Distinct (%)44.6%
Missing4
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean19.30357143
Minimum1
Maximum340
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size608.0 B
2022-09-05T21:42:23.207832image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q315.5
95-th percentile59
Maximum340
Range339
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation47.44639833
Coefficient of variation (CV)2.457907776
Kurtosis39.32483781
Mean19.30357143
Median Absolute Deviation (MAD)4
Skewness5.917135455
Sum1081
Variance2251.160714
MonotonicityNot monotonic
2022-09-05T21:42:23.302327image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
38
13.3%
47
11.7%
15
 
8.3%
64
 
6.7%
24
 
6.7%
53
 
5.0%
92
 
3.3%
132
 
3.3%
172
 
3.3%
472
 
3.3%
Other values (15)17
28.3%
(Missing)4
 
6.7%
ValueCountFrequency (%)
15
8.3%
24
6.7%
38
13.3%
47
11.7%
53
 
5.0%
64
6.7%
81
 
1.7%
92
 
3.3%
102
 
3.3%
111
 
1.7%
ValueCountFrequency (%)
3401
1.7%
871
1.7%
831
1.7%
511
1.7%
501
1.7%
472
3.3%
281
1.7%
251
1.7%
212
3.3%
191
1.7%

type
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size608.0 B
regular
56 
insignificant_special
 
4

Length

Max length21
Median length7
Mean length7.933333333
Min length7

Characters and Unicode

Total characters476
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular56
93.3%
insignificant_special4
 
6.7%

Length

2022-09-05T21:42:23.390927image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:42:23.470690image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
regular56
93.3%
insignificant_special4
 
6.7%

Most occurring characters

ValueCountFrequency (%)
r112
23.5%
a64
13.4%
e60
12.6%
g60
12.6%
l60
12.6%
u56
11.8%
i20
 
4.2%
n12
 
2.5%
s8
 
1.7%
c8
 
1.7%
Other values (4)16
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter472
99.2%
Connector Punctuation4
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r112
23.7%
a64
13.6%
e60
12.7%
g60
12.7%
l60
12.7%
u56
11.9%
i20
 
4.2%
n12
 
2.5%
s8
 
1.7%
c8
 
1.7%
Other values (3)12
 
2.5%
Connector Punctuation
ValueCountFrequency (%)
_4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin472
99.2%
Common4
 
0.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
r112
23.7%
a64
13.6%
e60
12.7%
g60
12.7%
l60
12.7%
u56
11.9%
i20
 
4.2%
n12
 
2.5%
s8
 
1.7%
c8
 
1.7%
Other values (3)12
 
2.5%
Common
ValueCountFrequency (%)
_4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII476
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r112
23.5%
a64
13.4%
e60
12.6%
g60
12.6%
l60
12.6%
u56
11.8%
i20
 
4.2%
n12
 
2.5%
s8
 
1.7%
c8
 
1.7%
Other values (4)16
 
3.4%

airdate
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size608.0 B
2020-12-13
60 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters600
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-13
2nd row2020-12-13
3rd row2020-12-13
4th row2020-12-13
5th row2020-12-13

Common Values

ValueCountFrequency (%)
2020-12-1360
100.0%

Length

2022-09-05T21:42:23.540396image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:42:23.615229image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-1360
100.0%

Most occurring characters

ValueCountFrequency (%)
2180
30.0%
0120
20.0%
-120
20.0%
1120
20.0%
360
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number480
80.0%
Dash Punctuation120
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2180
37.5%
0120
25.0%
1120
25.0%
360
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-120
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common600
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2180
30.0%
0120
20.0%
-120
20.0%
1120
20.0%
360
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII600
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2180
30.0%
0120
20.0%
-120
20.0%
1120
20.0%
360
 
10.0%

airtime
Categorical

HIGH CORRELATION

Distinct11
Distinct (%)18.3%
Missing0
Missing (%)0.0%
Memory size608.0 B
43 
06:00
10:00
 
3
12:00
 
2
17:00
 
1
Other values (6)

Length

Max length5
Median length0
Mean length1.416666667
Min length0

Characters and Unicode

Total characters85
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)11.7%

Sample

1st row
2nd row12:00
3rd row10:00
4th row10:00
5th row10:00

Common Values

ValueCountFrequency (%)
43
71.7%
06:005
 
8.3%
10:003
 
5.0%
12:002
 
3.3%
17:001
 
1.7%
21:101
 
1.7%
14:001
 
1.7%
13:001
 
1.7%
22:051
 
1.7%
20:001
 
1.7%

Length

2022-09-05T21:42:23.682613image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
06:005
29.4%
10:003
17.6%
12:002
 
11.8%
17:001
 
5.9%
21:101
 
5.9%
14:001
 
5.9%
13:001
 
5.9%
22:051
 
5.9%
20:001
 
5.9%
22:001
 
5.9%

Most occurring characters

ValueCountFrequency (%)
041
48.2%
:17
20.0%
110
 
11.8%
28
 
9.4%
65
 
5.9%
71
 
1.2%
41
 
1.2%
31
 
1.2%
51
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number68
80.0%
Other Punctuation17
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
041
60.3%
110
 
14.7%
28
 
11.8%
65
 
7.4%
71
 
1.5%
41
 
1.5%
31
 
1.5%
51
 
1.5%
Other Punctuation
ValueCountFrequency (%)
:17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common85
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
041
48.2%
:17
20.0%
110
 
11.8%
28
 
9.4%
65
 
5.9%
71
 
1.2%
41
 
1.2%
31
 
1.2%
51
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII85
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
041
48.2%
:17
20.0%
110
 
11.8%
28
 
9.4%
65
 
5.9%
71
 
1.2%
41
 
1.2%
31
 
1.2%
51
 
1.2%

airstamp
Categorical

HIGH CORRELATION

Distinct14
Distinct (%)23.3%
Missing0
Missing (%)0.0%
Memory size608.0 B
2020-12-13T12:00:00+00:00
23 
2020-12-13T11:00:00+00:00
2020-12-13T04:00:00+00:00
2020-12-13T05:00:00+00:00
2020-12-13T17:00:00+00:00
Other values (9)
12 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters1500
Distinct characters12
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)11.7%

Sample

1st row2020-12-13T00:00:00+00:00
2nd row2020-12-13T00:00:00+00:00
3rd row2020-12-13T02:00:00+00:00
4th row2020-12-13T02:00:00+00:00
5th row2020-12-13T02:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-13T12:00:00+00:0023
38.3%
2020-12-13T11:00:00+00:008
 
13.3%
2020-12-13T04:00:00+00:007
 
11.7%
2020-12-13T05:00:00+00:005
 
8.3%
2020-12-13T17:00:00+00:005
 
8.3%
2020-12-13T02:00:00+00:003
 
5.0%
2020-12-13T00:00:00+00:002
 
3.3%
2020-12-13T03:00:00+00:001
 
1.7%
2020-12-13T08:00:00+00:001
 
1.7%
2020-12-13T10:10:00+00:001
 
1.7%
Other values (4)4
 
6.7%

Length

2022-09-05T21:42:23.759641image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-13t12:00:00+00:0023
38.3%
2020-12-13t11:00:00+00:008
 
13.3%
2020-12-13t04:00:00+00:007
 
11.7%
2020-12-13t05:00:00+00:005
 
8.3%
2020-12-13t17:00:00+00:005
 
8.3%
2020-12-13t02:00:00+00:003
 
5.0%
2020-12-13t00:00:00+00:002
 
3.3%
2020-12-13t03:00:00+00:001
 
1.7%
2020-12-13t08:00:00+00:001
 
1.7%
2020-12-13t10:10:00+00:001
 
1.7%
Other values (4)4
 
6.7%

Most occurring characters

ValueCountFrequency (%)
0622
41.5%
2207
 
13.8%
:180
 
12.0%
1169
 
11.3%
-120
 
8.0%
360
 
4.0%
T60
 
4.0%
+60
 
4.0%
410
 
0.7%
56
 
0.4%
Other values (2)6
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1080
72.0%
Other Punctuation180
 
12.0%
Dash Punctuation120
 
8.0%
Uppercase Letter60
 
4.0%
Math Symbol60
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0622
57.6%
2207
 
19.2%
1169
 
15.6%
360
 
5.6%
410
 
0.9%
56
 
0.6%
75
 
0.5%
81
 
0.1%
Other Punctuation
ValueCountFrequency (%)
:180
100.0%
Dash Punctuation
ValueCountFrequency (%)
-120
100.0%
Uppercase Letter
ValueCountFrequency (%)
T60
100.0%
Math Symbol
ValueCountFrequency (%)
+60
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1440
96.0%
Latin60
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0622
43.2%
2207
 
14.4%
:180
 
12.5%
1169
 
11.7%
-120
 
8.3%
360
 
4.2%
+60
 
4.2%
410
 
0.7%
56
 
0.4%
75
 
0.3%
Latin
ValueCountFrequency (%)
T60
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0622
41.5%
2207
 
13.8%
:180
 
12.0%
1169
 
11.3%
-120
 
8.0%
360
 
4.0%
T60
 
4.0%
+60
 
4.0%
410
 
0.7%
56
 
0.4%
Other values (2)6
 
0.4%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct36
Distinct (%)66.7%
Missing6
Missing (%)10.0%
Infinite0
Infinite (%)0.0%
Mean41.98148148
Minimum4
Maximum184
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size608.0 B
2022-09-05T21:42:23.848254image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile7
Q114.25
median40
Q355.75
95-th percentile120
Maximum184
Range180
Interquartile range (IQR)41.5

Descriptive statistics

Standard deviation35.85794338
Coefficient of variation (CV)0.8541371603
Kurtosis4.025912248
Mean41.98148148
Median Absolute Deviation (MAD)20
Skewness1.747549859
Sum2267
Variance1285.792103
MonotonicityNot monotonic
2022-09-05T21:42:23.947915image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
76
 
10.0%
604
 
6.7%
453
 
5.0%
403
 
5.0%
1203
 
5.0%
502
 
3.3%
202
 
3.3%
432
 
3.3%
252
 
3.3%
191
 
1.7%
Other values (26)26
43.3%
(Missing)6
 
10.0%
ValueCountFrequency (%)
41
 
1.7%
61
 
1.7%
76
10.0%
81
 
1.7%
91
 
1.7%
111
 
1.7%
121
 
1.7%
131
 
1.7%
141
 
1.7%
151
 
1.7%
ValueCountFrequency (%)
1841
 
1.7%
1203
5.0%
1081
 
1.7%
901
 
1.7%
641
 
1.7%
621
 
1.7%
604
6.7%
581
 
1.7%
561
 
1.7%
551
 
1.7%

summary
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct16
Distinct (%)100.0%
Missing44
Missing (%)73.3%
Memory size608.0 B
<p>Struggling to get any more information from Ashley, Rex turns to a forensic psychologist for answers. A date for trial is set, but Ashley makes a shocking announcement.</p>
 
1
<p>On a journey to find love, Chance invites 15 beautiful "ladies" into his home. Each week he will put the hopefuls through various challenges to test their compatibility among other things. However, with constant infighting between the contestants, will Chance be able to finally find his happily ever after?</p>
 
1
<p>For King &amp; Country, Zach Williams, Mandisa, Chris Tomlin, Hillsong United, Joshua Aaron, The Bonner Family, The Piano Guys, Stephen McWhirter/Jason Clayborn, Phil Wickham, Matt Maher...how's that for a lineup of music artists celebrating Christmas with The Chosen? To honor the birth of Christ, and to commemorate the humble yet history-altering beginnings of The Greatest Story Ever Told, these musicians all performed their favorite Christmas songs, some on the incredible Jerusalem set of Season 2 of The Chosen. Join us on December 13th, where you'll not only see these performances, along with a special presentation of the Christmas short film that launched The Chosen, you'll also see a sneak peek of highlights of Season 2!</p>
 
1
<p>Filming for the drama Tamaki and Sogo are co-starring in is going well. However, Sogo continues to worry about his encounter with Tamaki's younger sister, which he hasn't been able to tell anyone about. On the final day of the special unit's joint practice, Tamaki is shocked to discover that Sogo couldn't trust him emough to tell him about Aya.</p>
 
1
<p>The TikTok mansion plays a wild game of Kiss or Truth.</p>
 
1
Other values (11)
11 

Length

Max length1021
Median length185.5
Mean length263.4375
Min length61

Characters and Unicode

Total characters4215
Distinct characters76
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)100.0%

Sample

1st row<p>Märtha does not know if she will go home to Norway after the war. Before she can start a new life, she must fight one last battle.</p>
2nd row<p>Throughout the dumpster fire that was 2020, Sammy J and his team turned up week in, week out to deliver three minutes of topical satire. Join Sammy J and friends as they look back on an objectively hideous twelve months.</p>
3rd row<p>After an argument, Anders suddenly realizes that Mio has begun to doubt their relationship.</p>
4th row<p>Elena and Paco discover that a local mirror is haunted. When Father Vergara spends the night investigating the mirror's trickery, he risks getting swept into its deathly portal.</p>
5th row<p>Given a deadline to clear up the Helen Nilsson case by the new boss at Kristianstad, Pelle and his team are under pressure.</p>

Common Values

ValueCountFrequency (%)
<p>Struggling to get any more information from Ashley, Rex turns to a forensic psychologist for answers. A date for trial is set, but Ashley makes a shocking announcement.</p>1
 
1.7%
<p>On a journey to find love, Chance invites 15 beautiful "ladies" into his home. Each week he will put the hopefuls through various challenges to test their compatibility among other things. However, with constant infighting between the contestants, will Chance be able to finally find his happily ever after?</p>1
 
1.7%
<p>For King &amp; Country, Zach Williams, Mandisa, Chris Tomlin, Hillsong United, Joshua Aaron, The Bonner Family, The Piano Guys, Stephen McWhirter/Jason Clayborn, Phil Wickham, Matt Maher...how's that for a lineup of music artists celebrating Christmas with The Chosen? To honor the birth of Christ, and to commemorate the humble yet history-altering beginnings of The Greatest Story Ever Told, these musicians all performed their favorite Christmas songs, some on the incredible Jerusalem set of Season 2 of The Chosen. Join us on December 13th, where you'll not only see these performances, along with a special presentation of the Christmas short film that launched The Chosen, you'll also see a sneak peek of highlights of Season 2!</p>1
 
1.7%
<p>Filming for the drama Tamaki and Sogo are co-starring in is going well. However, Sogo continues to worry about his encounter with Tamaki's younger sister, which he hasn't been able to tell anyone about. On the final day of the special unit's joint practice, Tamaki is shocked to discover that Sogo couldn't trust him emough to tell him about Aya.</p>1
 
1.7%
<p>The TikTok mansion plays a wild game of Kiss or Truth.</p>1
 
1.7%
<p>The crew meets their nemesis face to tentacle, and the Grand Minister of Agriculture tries the diplomatic approach…key word tries.</p>1
 
1.7%
<p>Ashley's new daughter arrives, but their time together is cut short when Ashley is remanded into custody. Rex and the prosecution engage in one final battle over Ashley's freedom.</p>1
 
1.7%
<p>Rex searches for evidence to implicate Kennard in the crime. Details of Ashley and Kennard's past reveal why she might be covering up for him. Kennard finally breaks his silence.</p>1
 
1.7%
<p>Märtha does not know if she will go home to Norway after the war. Before she can start a new life, she must fight one last battle.</p>1
 
1.7%
<p>Ashley Ard has been dubbed ‘The Most Hated Woman in Alaska' after being accused of killing her newborn baby. She pleads not guilty, and her lawyer draws attention to her ex-husband.</p>1
 
1.7%
Other values (6)6
 
10.0%
(Missing)44
73.3%

Length

2022-09-05T21:42:24.046836image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the31
 
4.6%
to22
 
3.2%
of17
 
2.5%
and14
 
2.1%
a13
 
1.9%
on7
 
1.0%
that7
 
1.0%
is7
 
1.0%
for7
 
1.0%
his6
 
0.9%
Other values (417)546
80.6%

Most occurring characters

ValueCountFrequency (%)
661
15.7%
e377
 
8.9%
t267
 
6.3%
a245
 
5.8%
o237
 
5.6%
i225
 
5.3%
n218
 
5.2%
r202
 
4.8%
s199
 
4.7%
h178
 
4.2%
Other values (66)1406
33.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3077
73.0%
Space Separator661
 
15.7%
Uppercase Letter259
 
6.1%
Other Punctuation127
 
3.0%
Math Symbol64
 
1.5%
Decimal Number12
 
0.3%
Dash Punctuation8
 
0.2%
Close Punctuation3
 
0.1%
Open Punctuation3
 
0.1%
Initial Punctuation1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e377
12.3%
t267
 
8.7%
a245
 
8.0%
o237
 
7.7%
i225
 
7.3%
n218
 
7.1%
r202
 
6.6%
s199
 
6.5%
h178
 
5.8%
l135
 
4.4%
Other values (17)794
25.8%
Uppercase Letter
ValueCountFrequency (%)
T33
 
12.7%
A26
 
10.0%
C21
 
8.1%
S17
 
6.6%
O14
 
5.4%
G13
 
5.0%
E13
 
5.0%
R12
 
4.6%
M11
 
4.2%
H11
 
4.2%
Other values (14)88
34.0%
Other Punctuation
ValueCountFrequency (%)
,43
33.9%
.40
31.5%
/17
 
13.4%
'15
 
11.8%
?4
 
3.1%
"2
 
1.6%
@1
 
0.8%
:1
 
0.8%
1
 
0.8%
!1
 
0.8%
Other values (2)2
 
1.6%
Decimal Number
ValueCountFrequency (%)
24
33.3%
13
25.0%
02
16.7%
51
 
8.3%
31
 
8.3%
91
 
8.3%
Math Symbol
ValueCountFrequency (%)
<32
50.0%
>32
50.0%
Space Separator
ValueCountFrequency (%)
661
100.0%
Dash Punctuation
ValueCountFrequency (%)
-8
100.0%
Close Punctuation
ValueCountFrequency (%)
)3
100.0%
Open Punctuation
ValueCountFrequency (%)
(3
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3336
79.1%
Common879
 
20.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e377
 
11.3%
t267
 
8.0%
a245
 
7.3%
o237
 
7.1%
i225
 
6.7%
n218
 
6.5%
r202
 
6.1%
s199
 
6.0%
h178
 
5.3%
l135
 
4.0%
Other values (41)1053
31.6%
Common
ValueCountFrequency (%)
661
75.2%
,43
 
4.9%
.40
 
4.6%
<32
 
3.6%
>32
 
3.6%
/17
 
1.9%
'15
 
1.7%
-8
 
0.9%
?4
 
0.5%
24
 
0.5%
Other values (15)23
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII4212
99.9%
Punctuation2
 
< 0.1%
None1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
661
15.7%
e377
 
9.0%
t267
 
6.3%
a245
 
5.8%
o237
 
5.6%
i225
 
5.3%
n218
 
5.2%
r202
 
4.8%
s199
 
4.7%
h178
 
4.2%
Other values (63)1403
33.3%
Punctuation
ValueCountFrequency (%)
1
50.0%
1
50.0%
None
ValueCountFrequency (%)
ä1
100.0%

rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct2
Distinct (%)100.0%
Missing58
Missing (%)96.7%
Memory size608.0 B
8.0
9.0

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters6
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row8.0
2nd row9.0

Common Values

ValueCountFrequency (%)
8.01
 
1.7%
9.01
 
1.7%
(Missing)58
96.7%

Length

2022-09-05T21:42:24.137383image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:42:24.225650image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
8.01
50.0%
9.01
50.0%

Most occurring characters

ValueCountFrequency (%)
.2
33.3%
02
33.3%
81
16.7%
91
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number4
66.7%
Other Punctuation2
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
02
50.0%
81
25.0%
91
25.0%
Other Punctuation
ValueCountFrequency (%)
.2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
.2
33.3%
02
33.3%
81
16.7%
91
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
.2
33.3%
02
33.3%
81
16.7%
91
16.7%

image.medium
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct25
Distinct (%)100.0%
Missing35
Missing (%)58.3%
Memory size608.0 B
https://static.tvmaze.com/uploads/images/medium_landscape/353/883108.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/382/955840.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/285/714232.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/393/983420.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/389/973509.jpg
 
1
Other values (20)
20 

Length

Max length73
Median length72
Mean length72.08
Min length72

Characters and Unicode

Total characters1802
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_landscape/353/883108.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/284/711895.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726347.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/288/721872.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/290/727207.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/353/883108.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/medium_landscape/382/955840.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/medium_landscape/285/714232.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/medium_landscape/393/983420.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/medium_landscape/389/973509.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/medium_landscape/291/729375.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/medium_landscape/291/729376.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/medium_landscape/291/729377.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/medium_landscape/291/729378.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/medium_landscape/291/729938.jpg1
 
1.7%
Other values (15)15
25.0%
(Missing)35
58.3%

Length

2022-09-05T21:42:24.300604image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/353/883108.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/medium_landscape/401/1003922.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/medium_landscape/284/711895.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726347.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/medium_landscape/288/721872.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/medium_landscape/290/727207.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/medium_landscape/290/727208.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/medium_landscape/288/722149.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/medium_landscape/291/729726.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/medium_landscape/288/721850.jpg1
 
4.0%
Other values (15)15
60.0%

Most occurring characters

ValueCountFrequency (%)
/175
 
9.7%
a150
 
8.3%
m125
 
6.9%
s125
 
6.9%
t125
 
6.9%
p100
 
5.5%
e100
 
5.5%
.75
 
4.2%
d75
 
4.2%
c75
 
4.2%
Other values (22)677
37.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1275
70.8%
Other Punctuation275
 
15.3%
Decimal Number227
 
12.6%
Connector Punctuation25
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a150
11.8%
m125
9.8%
s125
9.8%
t125
9.8%
p100
 
7.8%
e100
 
7.8%
d75
 
5.9%
c75
 
5.9%
i75
 
5.9%
g50
 
3.9%
Other values (8)275
21.6%
Decimal Number
ValueCountFrequency (%)
250
22.0%
832
14.1%
732
14.1%
927
11.9%
124
10.6%
318
 
7.9%
017
 
7.5%
510
 
4.4%
49
 
4.0%
68
 
3.5%
Other Punctuation
ValueCountFrequency (%)
/175
63.6%
.75
27.3%
:25
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1275
70.8%
Common527
29.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a150
11.8%
m125
9.8%
s125
9.8%
t125
9.8%
p100
 
7.8%
e100
 
7.8%
d75
 
5.9%
c75
 
5.9%
i75
 
5.9%
g50
 
3.9%
Other values (8)275
21.6%
Common
ValueCountFrequency (%)
/175
33.2%
.75
14.2%
250
 
9.5%
832
 
6.1%
732
 
6.1%
927
 
5.1%
_25
 
4.7%
:25
 
4.7%
124
 
4.6%
318
 
3.4%
Other values (4)44
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII1802
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/175
 
9.7%
a150
 
8.3%
m125
 
6.9%
s125
 
6.9%
t125
 
6.9%
p100
 
5.5%
e100
 
5.5%
.75
 
4.2%
d75
 
4.2%
c75
 
4.2%
Other values (22)677
37.6%

image.original
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct25
Distinct (%)100.0%
Missing35
Missing (%)58.3%
Memory size608.0 B
https://static.tvmaze.com/uploads/images/original_untouched/353/883108.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/382/955840.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/285/714232.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/393/983420.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/389/973509.jpg
 
1
Other values (20)
20 

Length

Max length75
Median length74
Mean length74.08
Min length74

Characters and Unicode

Total characters1852
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/353/883108.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/284/711895.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/290/726347.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/288/721872.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/290/727207.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/353/883108.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/original_untouched/382/955840.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/original_untouched/285/714232.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/original_untouched/393/983420.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/original_untouched/389/973509.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/original_untouched/291/729375.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/original_untouched/291/729376.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/original_untouched/291/729377.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/original_untouched/291/729378.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/original_untouched/291/729938.jpg1
 
1.7%
Other values (15)15
25.0%
(Missing)35
58.3%

Length

2022-09-05T21:42:24.383538image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/353/883108.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/original_untouched/401/1003922.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/original_untouched/284/711895.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/original_untouched/290/726347.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/original_untouched/288/721872.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/original_untouched/290/727207.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/original_untouched/290/727208.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/original_untouched/288/722149.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/original_untouched/291/729726.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/original_untouched/288/721850.jpg1
 
4.0%
Other values (15)15
60.0%

Most occurring characters

ValueCountFrequency (%)
/175
 
9.4%
t150
 
8.1%
a125
 
6.7%
s100
 
5.4%
o100
 
5.4%
i100
 
5.4%
m75
 
4.0%
u75
 
4.0%
e75
 
4.0%
g75
 
4.0%
Other values (23)802
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1325
71.5%
Other Punctuation275
 
14.8%
Decimal Number227
 
12.3%
Connector Punctuation25
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t150
 
11.3%
a125
 
9.4%
s100
 
7.5%
o100
 
7.5%
i100
 
7.5%
m75
 
5.7%
u75
 
5.7%
e75
 
5.7%
g75
 
5.7%
c75
 
5.7%
Other values (9)375
28.3%
Decimal Number
ValueCountFrequency (%)
250
22.0%
832
14.1%
732
14.1%
927
11.9%
124
10.6%
318
 
7.9%
017
 
7.5%
510
 
4.4%
49
 
4.0%
68
 
3.5%
Other Punctuation
ValueCountFrequency (%)
/175
63.6%
.75
27.3%
:25
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1325
71.5%
Common527
 
28.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t150
 
11.3%
a125
 
9.4%
s100
 
7.5%
o100
 
7.5%
i100
 
7.5%
m75
 
5.7%
u75
 
5.7%
e75
 
5.7%
g75
 
5.7%
c75
 
5.7%
Other values (9)375
28.3%
Common
ValueCountFrequency (%)
/175
33.2%
.75
14.2%
250
 
9.5%
832
 
6.1%
732
 
6.1%
927
 
5.1%
_25
 
4.7%
:25
 
4.7%
124
 
4.6%
318
 
3.4%
Other values (4)44
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII1852
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/175
 
9.4%
t150
 
8.1%
a125
 
6.7%
s100
 
5.4%
o100
 
5.4%
i100
 
5.4%
m75
 
4.0%
u75
 
4.0%
e75
 
4.0%
g75
 
4.0%
Other values (23)802
43.3%

_links.self.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size608.0 B
https://api.tvmaze.com/episodes/2121268
 
1
https://api.tvmaze.com/episodes/1985046
 
1
https://api.tvmaze.com/episodes/2111705
 
1
https://api.tvmaze.com/episodes/1985115
 
1
https://api.tvmaze.com/episodes/1964447
 
1
Other values (55)
55 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters2340
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2121268
2nd rowhttps://api.tvmaze.com/episodes/1985046
3rd rowhttps://api.tvmaze.com/episodes/1956339
4th rowhttps://api.tvmaze.com/episodes/1985601
5th rowhttps://api.tvmaze.com/episodes/2052508

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/21212681
 
1.7%
https://api.tvmaze.com/episodes/19850461
 
1.7%
https://api.tvmaze.com/episodes/21117051
 
1.7%
https://api.tvmaze.com/episodes/19851151
 
1.7%
https://api.tvmaze.com/episodes/19644471
 
1.7%
https://api.tvmaze.com/episodes/20372791
 
1.7%
https://api.tvmaze.com/episodes/19850931
 
1.7%
https://api.tvmaze.com/episodes/19830441
 
1.7%
https://api.tvmaze.com/episodes/19968161
 
1.7%
https://api.tvmaze.com/episodes/19972991
 
1.7%
Other values (50)50
83.3%

Length

2022-09-05T21:42:24.467206image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/21212681
 
1.7%
https://api.tvmaze.com/episodes/19850461
 
1.7%
https://api.tvmaze.com/episodes/19773211
 
1.7%
https://api.tvmaze.com/episodes/19563391
 
1.7%
https://api.tvmaze.com/episodes/19856011
 
1.7%
https://api.tvmaze.com/episodes/20525081
 
1.7%
https://api.tvmaze.com/episodes/19659241
 
1.7%
https://api.tvmaze.com/episodes/20123211
 
1.7%
https://api.tvmaze.com/episodes/20714711
 
1.7%
https://api.tvmaze.com/episodes/20714721
 
1.7%
Other values (50)50
83.3%

Most occurring characters

ValueCountFrequency (%)
/240
 
10.3%
t180
 
7.7%
p180
 
7.7%
s180
 
7.7%
e180
 
7.7%
a120
 
5.1%
i120
 
5.1%
.120
 
5.1%
m120
 
5.1%
o120
 
5.1%
Other values (16)780
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1500
64.1%
Other Punctuation420
 
17.9%
Decimal Number420
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t180
12.0%
p180
12.0%
s180
12.0%
e180
12.0%
a120
8.0%
i120
8.0%
m120
8.0%
o120
8.0%
h60
 
4.0%
d60
 
4.0%
Other values (3)180
12.0%
Decimal Number
ValueCountFrequency (%)
176
18.1%
957
13.6%
254
12.9%
742
10.0%
537
8.8%
035
8.3%
633
7.9%
432
7.6%
829
 
6.9%
325
 
6.0%
Other Punctuation
ValueCountFrequency (%)
/240
57.1%
.120
28.6%
:60
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin1500
64.1%
Common840
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/240
28.6%
.120
14.3%
176
 
9.0%
:60
 
7.1%
957
 
6.8%
254
 
6.4%
742
 
5.0%
537
 
4.4%
035
 
4.2%
633
 
3.9%
Other values (3)86
 
10.2%
Latin
ValueCountFrequency (%)
t180
12.0%
p180
12.0%
s180
12.0%
e180
12.0%
a120
8.0%
i120
8.0%
m120
8.0%
o120
8.0%
h60
 
4.0%
d60
 
4.0%
Other values (3)180
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2340
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/240
 
10.3%
t180
 
7.7%
p180
 
7.7%
s180
 
7.7%
e180
 
7.7%
a120
 
5.1%
i120
 
5.1%
.120
 
5.1%
m120
 
5.1%
o120
 
5.1%
Other values (16)780
33.3%

_embedded.show.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct48
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47277.31667
Minimum12906
Maximum61755
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size608.0 B
2022-09-05T21:42:24.565115image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum12906
5-th percentile24859.5
Q143190.5
median51682.5
Q352978
95-th percentile59425.65
Maximum61755
Range48849
Interquartile range (IQR)9787.5

Descriptive statistics

Standard deviation10239.03495
Coefficient of variation (CV)0.2165739444
Kurtosis2.058347153
Mean47277.31667
Median Absolute Deviation (MAD)3448.5
Skewness-1.434617756
Sum2836639
Variance104837836.7
MonotonicityNot monotonic
2022-09-05T21:42:24.674603image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
547626
 
10.0%
527724
 
6.7%
440573
 
5.0%
524233
 
5.0%
381991
 
1.7%
521481
 
1.7%
523031
 
1.7%
527371
 
1.7%
528581
 
1.7%
533381
 
1.7%
Other values (38)38
63.3%
ValueCountFrequency (%)
129061
1.7%
187521
1.7%
228931
1.7%
249631
1.7%
306061
1.7%
322141
1.7%
334631
1.7%
349011
1.7%
369071
1.7%
381991
1.7%
ValueCountFrequency (%)
617551
 
1.7%
602461
 
1.7%
599511
 
1.7%
593981
 
1.7%
583561
 
1.7%
578741
 
1.7%
547626
10.0%
540331
 
1.7%
537351
 
1.7%
533381
 
1.7%

_embedded.show.url
Categorical

HIGH CORRELATION

Distinct48
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Memory size608.0 B
https://www.tvmaze.com/shows/54762/youths-in-the-breeze
https://www.tvmaze.com/shows/52772/accused-a-mother-on-trial
 
4
https://www.tvmaze.com/shows/44057/hjerteslag
 
3
https://www.tvmaze.com/shows/52423/aukrust-gud-velsigne-var-herre
 
3
https://www.tvmaze.com/shows/38199/fiksiki
 
1
Other values (43)
43 

Length

Max length77
Median length61
Mean length51.1
Min length41

Characters and Unicode

Total characters3066
Distinct characters39
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)73.3%

Sample

1st rowhttps://www.tvmaze.com/shows/38199/fiksiki
2nd rowhttps://www.tvmaze.com/shows/47865/a-seba-znau
3rd rowhttps://www.tvmaze.com/shows/51471/hero-return
4th rowhttps://www.tvmaze.com/shows/52178/swallowed-star
5th rowhttps://www.tvmaze.com/shows/54033/wu-shen-zhu-zai

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/54762/youths-in-the-breeze6
 
10.0%
https://www.tvmaze.com/shows/52772/accused-a-mother-on-trial4
 
6.7%
https://www.tvmaze.com/shows/44057/hjerteslag3
 
5.0%
https://www.tvmaze.com/shows/52423/aukrust-gud-velsigne-var-herre3
 
5.0%
https://www.tvmaze.com/shows/38199/fiksiki1
 
1.7%
https://www.tvmaze.com/shows/52148/ultra-galaxy-fight-the-absolute-conspiracy1
 
1.7%
https://www.tvmaze.com/shows/52303/pappas-pojkar1
 
1.7%
https://www.tvmaze.com/shows/52737/the-george-lucas-talk-show1
 
1.7%
https://www.tvmaze.com/shows/52858/laikykites-ten1
 
1.7%
https://www.tvmaze.com/shows/53338/el-anesa-farah1
 
1.7%
Other values (38)38
63.3%

Length

2022-09-05T21:42:24.779356image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/54762/youths-in-the-breeze6
 
10.0%
https://www.tvmaze.com/shows/52772/accused-a-mother-on-trial4
 
6.7%
https://www.tvmaze.com/shows/44057/hjerteslag3
 
5.0%
https://www.tvmaze.com/shows/52423/aukrust-gud-velsigne-var-herre3
 
5.0%
https://www.tvmaze.com/shows/34901/sammy-j1
 
1.7%
https://www.tvmaze.com/shows/47865/a-seba-znau1
 
1.7%
https://www.tvmaze.com/shows/51471/hero-return1
 
1.7%
https://www.tvmaze.com/shows/52178/swallowed-star1
 
1.7%
https://www.tvmaze.com/shows/54033/wu-shen-zhu-zai1
 
1.7%
https://www.tvmaze.com/shows/24963/new-japan-pro-wrestling1
 
1.7%
Other values (38)38
63.3%

Most occurring characters

ValueCountFrequency (%)
/300
 
9.8%
w252
 
8.2%
t243
 
7.9%
s238
 
7.8%
o173
 
5.6%
e172
 
5.6%
h160
 
5.2%
m139
 
4.5%
a136
 
4.4%
.120
 
3.9%
Other values (29)1133
37.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2174
70.9%
Other Punctuation480
 
15.7%
Decimal Number304
 
9.9%
Dash Punctuation108
 
3.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w252
11.6%
t243
11.2%
s238
10.9%
o173
 
8.0%
e172
 
7.9%
h160
 
7.4%
m139
 
6.4%
a136
 
6.3%
c86
 
4.0%
p75
 
3.4%
Other values (15)500
23.0%
Decimal Number
ValueCountFrequency (%)
546
15.1%
245
14.8%
445
14.8%
336
11.8%
733
10.9%
926
8.6%
120
6.6%
619
6.2%
017
 
5.6%
817
 
5.6%
Other Punctuation
ValueCountFrequency (%)
/300
62.5%
.120
 
25.0%
:60
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-108
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2174
70.9%
Common892
29.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
w252
11.6%
t243
11.2%
s238
10.9%
o173
 
8.0%
e172
 
7.9%
h160
 
7.4%
m139
 
6.4%
a136
 
6.3%
c86
 
4.0%
p75
 
3.4%
Other values (15)500
23.0%
Common
ValueCountFrequency (%)
/300
33.6%
.120
 
13.5%
-108
 
12.1%
:60
 
6.7%
546
 
5.2%
245
 
5.0%
445
 
5.0%
336
 
4.0%
733
 
3.7%
926
 
2.9%
Other values (4)73
 
8.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII3066
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/300
 
9.8%
w252
 
8.2%
t243
 
7.9%
s238
 
7.8%
o173
 
5.6%
e172
 
5.6%
h160
 
5.2%
m139
 
4.5%
a136
 
4.4%
.120
 
3.9%
Other values (29)1133
37.0%

_embedded.show.name
Categorical

HIGH CORRELATION

Distinct48
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Memory size608.0 B
Youths in the Breeze
Accused: A Mother on Trial
 
4
Hjerteslag
 
3
Aukrust - Gud velsigne vår Herre
 
3
Фиксики
 
1
Other values (43)
43 

Length

Max length43
Median length24
Mean length16.53333333
Min length6

Characters and Unicode

Total characters992
Distinct characters103
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)73.3%

Sample

1st rowФиксики
2nd rowЯ СЕБЯ ЗНАЮ!
3rd rowHero Return
4th rowSwallowed Star
5th rowWu Shen Zhu Zai

Common Values

ValueCountFrequency (%)
Youths in the Breeze6
 
10.0%
Accused: A Mother on Trial4
 
6.7%
Hjerteslag3
 
5.0%
Aukrust - Gud velsigne vår Herre3
 
5.0%
Фиксики1
 
1.7%
Ultra Galaxy Fight: The Absolute Conspiracy1
 
1.7%
Pappas pojkar1
 
1.7%
The George Lucas Talk Show1
 
1.7%
Laikykitės Ten1
 
1.7%
El Anesa Farah1
 
1.7%
Other values (38)38
63.3%

Length

2022-09-05T21:42:24.886065image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the10
 
5.8%
youths6
 
3.5%
breeze6
 
3.5%
in6
 
3.5%
mother5
 
2.9%
accused4
 
2.3%
a4
 
2.3%
on4
 
2.3%
trial4
 
2.3%
gud3
 
1.8%
Other values (107)119
69.6%

Most occurring characters

ValueCountFrequency (%)
111
 
11.2%
e105
 
10.6%
r58
 
5.8%
n51
 
5.1%
t48
 
4.8%
a45
 
4.5%
s43
 
4.3%
o43
 
4.3%
i42
 
4.2%
u33
 
3.3%
Other values (93)413
41.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter705
71.1%
Uppercase Letter150
 
15.1%
Space Separator111
 
11.2%
Other Punctuation14
 
1.4%
Decimal Number4
 
0.4%
Dash Punctuation3
 
0.3%
Close Punctuation2
 
0.2%
Currency Symbol2
 
0.2%
Open Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e105
14.9%
r58
 
8.2%
n51
 
7.2%
t48
 
6.8%
a45
 
6.4%
s43
 
6.1%
o43
 
6.1%
i42
 
6.0%
u33
 
4.7%
h31
 
4.4%
Other values (40)206
29.2%
Uppercase Letter
ValueCountFrequency (%)
A17
 
11.3%
T14
 
9.3%
S10
 
6.7%
M10
 
6.7%
B10
 
6.7%
H9
 
6.0%
W6
 
4.0%
Y6
 
4.0%
L5
 
3.3%
O5
 
3.3%
Other values (28)58
38.7%
Other Punctuation
ValueCountFrequency (%)
'5
35.7%
:5
35.7%
?1
 
7.1%
@1
 
7.1%
#1
 
7.1%
!1
 
7.1%
Decimal Number
ValueCountFrequency (%)
02
50.0%
31
25.0%
71
25.0%
Currency Symbol
ValueCountFrequency (%)
$1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
111
100.0%
Dash Punctuation
ValueCountFrequency (%)
-3
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin794
80.0%
Common137
 
13.8%
Cyrillic61
 
6.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e105
 
13.2%
r58
 
7.3%
n51
 
6.4%
t48
 
6.0%
a45
 
5.7%
s43
 
5.4%
o43
 
5.4%
i42
 
5.3%
u33
 
4.2%
h31
 
3.9%
Other values (44)295
37.2%
Cyrillic
ValueCountFrequency (%)
и7
 
11.5%
к6
 
9.8%
м3
 
4.9%
е3
 
4.9%
о3
 
4.9%
а3
 
4.9%
у3
 
4.9%
с3
 
4.9%
Я2
 
3.3%
я2
 
3.3%
Other values (24)26
42.6%
Common
ValueCountFrequency (%)
111
81.0%
'5
 
3.6%
:5
 
3.6%
-3
 
2.2%
)2
 
1.5%
02
 
1.5%
$1
 
0.7%
?1
 
0.7%
1
 
0.7%
@1
 
0.7%
Other values (5)5
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII921
92.8%
Cyrillic61
 
6.1%
None9
 
0.9%
Currency Symbols1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
111
 
12.1%
e105
 
11.4%
r58
 
6.3%
n51
 
5.5%
t48
 
5.2%
a45
 
4.9%
s43
 
4.7%
o43
 
4.7%
i42
 
4.6%
u33
 
3.6%
Other values (53)342
37.1%
Cyrillic
ValueCountFrequency (%)
и7
 
11.5%
к6
 
9.8%
м3
 
4.9%
е3
 
4.9%
о3
 
4.9%
а3
 
4.9%
у3
 
4.9%
с3
 
4.9%
Я2
 
3.3%
я2
 
3.3%
Other values (24)26
42.6%
None
ValueCountFrequency (%)
å4
44.4%
á2
22.2%
ö1
 
11.1%
ø1
 
11.1%
ė1
 
11.1%
Currency Symbols
ValueCountFrequency (%)
1
100.0%

_embedded.show.type
Categorical

HIGH CORRELATION

Distinct8
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size608.0 B
Scripted
27 
Documentary
11 
Talk Show
Animation
Reality
Other values (3)

Length

Max length11
Median length9
Mean length8.55
Min length4

Characters and Unicode

Total characters513
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAnimation
2nd rowTalk Show
3rd rowAnimation
4th rowAnimation
5th rowAnimation

Common Values

ValueCountFrequency (%)
Scripted27
45.0%
Documentary11
18.3%
Talk Show7
 
11.7%
Animation6
 
10.0%
Reality3
 
5.0%
Sports2
 
3.3%
Game Show2
 
3.3%
News2
 
3.3%

Length

2022-09-05T21:42:24.986662image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:42:25.090196image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
scripted27
39.1%
documentary11
15.9%
show9
 
13.0%
talk7
 
10.1%
animation6
 
8.7%
reality3
 
4.3%
sports2
 
2.9%
game2
 
2.9%
news2
 
2.9%

Most occurring characters

ValueCountFrequency (%)
t49
 
9.6%
e45
 
8.8%
i42
 
8.2%
r40
 
7.8%
S38
 
7.4%
c38
 
7.4%
a29
 
5.7%
p29
 
5.7%
o28
 
5.5%
d27
 
5.3%
Other values (16)148
28.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter435
84.8%
Uppercase Letter69
 
13.5%
Space Separator9
 
1.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t49
11.3%
e45
10.3%
i42
9.7%
r40
9.2%
c38
8.7%
a29
 
6.7%
p29
 
6.7%
o28
 
6.4%
d27
 
6.2%
n23
 
5.3%
Other values (8)85
19.5%
Uppercase Letter
ValueCountFrequency (%)
S38
55.1%
D11
 
15.9%
T7
 
10.1%
A6
 
8.7%
R3
 
4.3%
G2
 
2.9%
N2
 
2.9%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin504
98.2%
Common9
 
1.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
t49
 
9.7%
e45
 
8.9%
i42
 
8.3%
r40
 
7.9%
S38
 
7.5%
c38
 
7.5%
a29
 
5.8%
p29
 
5.8%
o28
 
5.6%
d27
 
5.4%
Other values (15)139
27.6%
Common
ValueCountFrequency (%)
9
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII513
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t49
 
9.6%
e45
 
8.8%
i42
 
8.2%
r40
 
7.8%
S38
 
7.4%
c38
 
7.4%
a29
 
5.7%
p29
 
5.7%
o28
 
5.5%
d27
 
5.3%
Other values (16)148
28.8%

_embedded.show.language
Categorical

HIGH CORRELATION

Distinct16
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Memory size608.0 B
English
16 
Norwegian
11 
Chinese
10 
Russian
Japanese
Other values (11)
15 

Length

Max length10
Median length7
Mean length7.466666667
Min length6

Characters and Unicode

Total characters448
Distinct characters33
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)13.3%

Sample

1st rowRussian
2nd rowRussian
3rd rowChinese
4th rowChinese
5th rowChinese

Common Values

ValueCountFrequency (%)
English16
26.7%
Norwegian11
18.3%
Chinese10
16.7%
Russian5
 
8.3%
Japanese3
 
5.0%
Spanish3
 
5.0%
Swedish2
 
3.3%
Arabic2
 
3.3%
Korean1
 
1.7%
Ukrainian1
 
1.7%
Other values (6)6
 
10.0%

Length

2022-09-05T21:42:25.185809image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
english16
26.7%
norwegian11
18.3%
chinese10
16.7%
russian5
 
8.3%
japanese3
 
5.0%
spanish3
 
5.0%
swedish2
 
3.3%
arabic2
 
3.3%
korean1
 
1.7%
ukrainian1
 
1.7%
Other values (6)6
 
10.0%

Most occurring characters

ValueCountFrequency (%)
n58
12.9%
i55
12.3%
s46
10.3%
e44
9.8%
a36
 
8.0%
h34
 
7.6%
g28
 
6.2%
r18
 
4.0%
E16
 
3.6%
l16
 
3.6%
Other values (23)97
21.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter388
86.6%
Uppercase Letter60
 
13.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n58
14.9%
i55
14.2%
s46
11.9%
e44
11.3%
a36
9.3%
h34
8.8%
g28
7.2%
r18
 
4.6%
l16
 
4.1%
o14
 
3.6%
Other values (9)39
10.1%
Uppercase Letter
ValueCountFrequency (%)
E16
26.7%
N11
18.3%
C10
16.7%
R6
 
10.0%
S5
 
8.3%
J3
 
5.0%
A2
 
3.3%
K1
 
1.7%
U1
 
1.7%
G1
 
1.7%
Other values (4)4
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
Latin448
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n58
12.9%
i55
12.3%
s46
10.3%
e44
9.8%
a36
 
8.0%
h34
 
7.6%
g28
 
6.2%
r18
 
4.0%
E16
 
3.6%
l16
 
3.6%
Other values (23)97
21.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII448
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n58
12.9%
i55
12.3%
s46
10.3%
e44
9.8%
a36
 
8.0%
h34
 
7.6%
g28
 
6.2%
r18
 
4.0%
E16
 
3.6%
l16
 
3.6%
Other values (23)97
21.7%

_embedded.show.genres
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size608.0 B

_embedded.show.status
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size608.0 B
Running
31 
Ended
21 
To Be Determined

Length

Max length16
Median length7
Mean length7.5
Min length5

Characters and Unicode

Total characters450
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRunning
2nd rowRunning
3rd rowRunning
4th rowRunning
5th rowRunning

Common Values

ValueCountFrequency (%)
Running31
51.7%
Ended21
35.0%
To Be Determined8
 
13.3%

Length

2022-09-05T21:42:25.272189image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:42:25.355417image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
running31
40.8%
ended21
27.6%
to8
 
10.5%
be8
 
10.5%
determined8
 
10.5%

Most occurring characters

ValueCountFrequency (%)
n122
27.1%
e53
11.8%
d50
11.1%
i39
 
8.7%
R31
 
6.9%
u31
 
6.9%
g31
 
6.9%
E21
 
4.7%
16
 
3.6%
T8
 
1.8%
Other values (6)48
 
10.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter358
79.6%
Uppercase Letter76
 
16.9%
Space Separator16
 
3.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n122
34.1%
e53
14.8%
d50
14.0%
i39
 
10.9%
u31
 
8.7%
g31
 
8.7%
o8
 
2.2%
t8
 
2.2%
r8
 
2.2%
m8
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
R31
40.8%
E21
27.6%
T8
 
10.5%
B8
 
10.5%
D8
 
10.5%
Space Separator
ValueCountFrequency (%)
16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin434
96.4%
Common16
 
3.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
n122
28.1%
e53
12.2%
d50
11.5%
i39
 
9.0%
R31
 
7.1%
u31
 
7.1%
g31
 
7.1%
E21
 
4.8%
T8
 
1.8%
o8
 
1.8%
Other values (5)40
 
9.2%
Common
ValueCountFrequency (%)
16
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII450
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n122
27.1%
e53
11.8%
d50
11.1%
i39
 
8.7%
R31
 
6.9%
u31
 
6.9%
g31
 
6.9%
E21
 
4.7%
16
 
3.6%
T8
 
1.8%
Other values (6)48
 
10.7%

_embedded.show.runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct17
Distinct (%)41.5%
Missing19
Missing (%)31.7%
Infinite0
Infinite (%)0.0%
Mean39.58536585
Minimum5
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size608.0 B
2022-09-05T21:42:25.427228image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile7
Q112
median30
Q350
95-th percentile120
Maximum180
Range175
Interquartile range (IQR)38

Descriptive statistics

Standard deviation37.6476929
Coefficient of variation (CV)0.9510507756
Kurtosis4.408448564
Mean39.58536585
Median Absolute Deviation (MAD)20
Skewness1.929710438
Sum1623
Variance1417.34878
MonotonicityNot monotonic
2022-09-05T21:42:25.515917image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
76
 
10.0%
506
 
10.0%
604
 
6.7%
304
 
6.7%
1203
 
5.0%
123
 
5.0%
453
 
5.0%
202
 
3.3%
402
 
3.3%
61
 
1.7%
Other values (7)7
 
11.7%
(Missing)19
31.7%
ValueCountFrequency (%)
51
 
1.7%
61
 
1.7%
76
10.0%
81
 
1.7%
91
 
1.7%
123
5.0%
151
 
1.7%
202
 
3.3%
221
 
1.7%
251
 
1.7%
ValueCountFrequency (%)
1801
 
1.7%
1203
5.0%
604
6.7%
506
10.0%
453
5.0%
402
 
3.3%
304
6.7%
251
 
1.7%
221
 
1.7%
202
 
3.3%

_embedded.show.averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct34
Distinct (%)60.7%
Missing4
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean39.21428571
Minimum4
Maximum188
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size608.0 B
2022-09-05T21:42:25.611917image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile6.75
Q111
median31.5
Q350
95-th percentile120
Maximum188
Range184
Interquartile range (IQR)39

Descriptive statistics

Standard deviation35.42814202
Coefficient of variation (CV)0.9034498875
Kurtosis5.187041607
Mean39.21428571
Median Absolute Deviation (MAD)20
Skewness1.953234533
Sum2196
Variance1255.153247
MonotonicityNot monotonic
2022-09-05T21:42:25.713523image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
76
 
10.0%
424
 
6.7%
483
 
5.0%
1203
 
5.0%
113
 
5.0%
603
 
5.0%
452
 
3.3%
292
 
3.3%
92
 
3.3%
502
 
3.3%
Other values (24)26
43.3%
(Missing)4
 
6.7%
ValueCountFrequency (%)
41
 
1.7%
51
 
1.7%
61
 
1.7%
76
10.0%
81
 
1.7%
92
 
3.3%
113
5.0%
122
 
3.3%
161
 
1.7%
181
 
1.7%
ValueCountFrequency (%)
1881
 
1.7%
1203
5.0%
981
 
1.7%
711
 
1.7%
641
 
1.7%
603
5.0%
591
 
1.7%
561
 
1.7%
551
 
1.7%
502
3.3%

_embedded.show.premiered
Categorical

HIGH CORRELATION

Distinct40
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size608.0 B
2020-12-13
14 
2020-11-29
2020-11-22
 
3
2019-08-15
 
3
2010-12-13
 
1
Other values (35)
35 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters600
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)60.0%

Sample

1st row2010-12-13
2nd row2020-05-01
3rd row2020-10-18
4th row2020-11-29
5th row2020-03-08

Common Values

ValueCountFrequency (%)
2020-12-1314
23.3%
2020-11-294
 
6.7%
2020-11-223
 
5.0%
2019-08-153
 
5.0%
2010-12-131
 
1.7%
2019-07-241
 
1.7%
2020-04-211
 
1.7%
2020-12-061
 
1.7%
2020-05-041
 
1.7%
2016-09-111
 
1.7%
Other values (30)30
50.0%

Length

2022-09-05T21:42:25.800553image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-1314
23.3%
2020-11-294
 
6.7%
2020-11-223
 
5.0%
2019-08-153
 
5.0%
2020-09-011
 
1.7%
2020-05-011
 
1.7%
2020-10-181
 
1.7%
2020-03-081
 
1.7%
2015-01-041
 
1.7%
2019-07-211
 
1.7%
Other values (30)30
50.0%

Most occurring characters

ValueCountFrequency (%)
0143
23.8%
2138
23.0%
-120
20.0%
1107
17.8%
925
 
4.2%
320
 
3.3%
513
 
2.2%
812
 
2.0%
48
 
1.3%
68
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number480
80.0%
Dash Punctuation120
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0143
29.8%
2138
28.7%
1107
22.3%
925
 
5.2%
320
 
4.2%
513
 
2.7%
812
 
2.5%
48
 
1.7%
68
 
1.7%
76
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
-120
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common600
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0143
23.8%
2138
23.0%
-120
20.0%
1107
17.8%
925
 
4.2%
320
 
3.3%
513
 
2.2%
812
 
2.0%
48
 
1.3%
68
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII600
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0143
23.8%
2138
23.0%
-120
20.0%
1107
17.8%
925
 
4.2%
320
 
3.3%
513
 
2.2%
812
 
2.0%
48
 
1.3%
68
 
1.3%

_embedded.show.ended
Categorical

HIGH CORRELATION
MISSING

Distinct7
Distinct (%)33.3%
Missing39
Missing (%)65.0%
Memory size608.0 B
2020-12-13
10 
2020-12-22
2020-12-24
 
1
2020-12-27
 
1
2020-10-25
 
1
Other values (2)

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters210
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)23.8%

Sample

1st row2020-12-22
2nd row2020-12-22
3rd row2020-12-22
4th row2020-12-22
5th row2020-12-22

Common Values

ValueCountFrequency (%)
2020-12-1310
 
16.7%
2020-12-226
 
10.0%
2020-12-241
 
1.7%
2020-12-271
 
1.7%
2020-10-251
 
1.7%
2021-01-311
 
1.7%
2021-11-281
 
1.7%
(Missing)39
65.0%

Length

2022-09-05T21:42:25.880951image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:42:25.978586image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-1310
47.6%
2020-12-226
28.6%
2020-12-241
 
4.8%
2020-12-271
 
4.8%
2020-10-251
 
4.8%
2021-01-311
 
4.8%
2021-11-281
 
4.8%

Most occurring characters

ValueCountFrequency (%)
276
36.2%
042
20.0%
-42
20.0%
135
16.7%
311
 
5.2%
41
 
0.5%
71
 
0.5%
51
 
0.5%
81
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number168
80.0%
Dash Punctuation42
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
276
45.2%
042
25.0%
135
20.8%
311
 
6.5%
41
 
0.6%
71
 
0.6%
51
 
0.6%
81
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
-42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common210
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
276
36.2%
042
20.0%
-42
20.0%
135
16.7%
311
 
5.2%
41
 
0.5%
71
 
0.5%
51
 
0.5%
81
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII210
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
276
36.2%
042
20.0%
-42
20.0%
135
16.7%
311
 
5.2%
41
 
0.5%
71
 
0.5%
51
 
0.5%
81
 
0.5%

_embedded.show.officialSite
Categorical

HIGH CORRELATION
MISSING

Distinct46
Distinct (%)79.3%
Missing2
Missing (%)3.3%
Memory size608.0 B
https://v.youku.com/v_show/id_XNDk4OTUxMzg1Mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef
https://www.bbc.co.uk/programmes/p08z34bl
 
4
https://play.tv2.no/programmer/serier/hjerteslag
 
3
https://tv.nrk.no/serie/aukrust-gud-velsigne-vaar-herre
 
3
https://www.youtube.com/channel/UC4g4YABfz_vEwmZLjtF2Zjw
 
1
Other values (41)
41 

Length

Max length105
Median length61
Mean length52.75862069
Min length20

Characters and Unicode

Total characters3060
Distinct characters68
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)72.4%

Sample

1st rowhttp://www.fixiki.ru
2nd rowhttps://premier.one/show/11906
3rd rowhttps://v.qq.com/detail/q/q72jd29a3oxflsr.html
4th rowhttps://v.qq.com/detail/3/324olz7ilvo2j5f.html
5th rowhttps://v.qq.com/detail/m/7q544xyrava3vxf.html

Common Values

ValueCountFrequency (%)
https://v.youku.com/v_show/id_XNDk4OTUxMzg1Mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef6
 
10.0%
https://www.bbc.co.uk/programmes/p08z34bl4
 
6.7%
https://play.tv2.no/programmer/serier/hjerteslag3
 
5.0%
https://tv.nrk.no/serie/aukrust-gud-velsigne-vaar-herre3
 
5.0%
https://www.youtube.com/channel/UC4g4YABfz_vEwmZLjtF2Zjw1
 
1.7%
http://m-78.jp/galaxy-fight/tac/1
 
1.7%
https://www.discoveryplus.se/program/pappas-pojkar1
 
1.7%
https://www.patrickcotnoir.com/glts1
 
1.7%
http://www.laisves.tv1
 
1.7%
https://shahid.mbc.net/en/series/Al-Anisa-Farah/series-3936341
 
1.7%
Other values (36)36
60.0%
(Missing)2
 
3.3%

Length

2022-09-05T21:42:26.079391image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://v.youku.com/v_show/id_xndk4otuxmzg1mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef6
 
10.3%
https://www.bbc.co.uk/programmes/p08z34bl4
 
6.9%
https://play.tv2.no/programmer/serier/hjerteslag3
 
5.2%
https://tv.nrk.no/serie/aukrust-gud-velsigne-vaar-herre3
 
5.2%
https://iview.abc.net.au/show/sammy-j1
 
1.7%
https://v.qq.com/detail/q/q72jd29a3oxflsr.html1
 
1.7%
https://v.qq.com/detail/3/324olz7ilvo2j5f.html1
 
1.7%
https://v.qq.com/detail/m/7q544xyrava3vxf.html1
 
1.7%
http://www.njpw1972.com1
 
1.7%
https://www.bilibili.com/bangumi/media/md43146221
 
1.7%
Other values (36)36
62.1%

Most occurring characters

ValueCountFrequency (%)
/246
 
8.0%
t211
 
6.9%
e190
 
6.2%
s173
 
5.7%
.140
 
4.6%
o129
 
4.2%
h121
 
4.0%
p114
 
3.7%
r114
 
3.7%
a113
 
3.7%
Other values (58)1509
49.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2106
68.8%
Other Punctuation460
 
15.0%
Decimal Number288
 
9.4%
Uppercase Letter104
 
3.4%
Dash Punctuation61
 
2.0%
Math Symbol27
 
0.9%
Connector Punctuation14
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t211
 
10.0%
e190
 
9.0%
s173
 
8.2%
o129
 
6.1%
h121
 
5.7%
p114
 
5.4%
r114
 
5.4%
a113
 
5.4%
i94
 
4.5%
w88
 
4.2%
Other values (16)759
36.0%
Uppercase Letter
ValueCountFrequency (%)
M12
11.5%
N11
10.6%
U10
 
9.6%
T9
 
8.7%
D8
 
7.7%
O7
 
6.7%
X7
 
6.7%
C5
 
4.8%
A5
 
4.8%
F4
 
3.8%
Other values (13)26
25.0%
Decimal Number
ValueCountFrequency (%)
456
19.4%
154
18.8%
353
18.4%
233
11.5%
022
 
7.6%
520
 
6.9%
618
 
6.2%
713
 
4.5%
910
 
3.5%
89
 
3.1%
Other Punctuation
ValueCountFrequency (%)
/246
53.5%
.140
30.4%
:58
 
12.6%
?8
 
1.7%
&7
 
1.5%
%1
 
0.2%
Dash Punctuation
ValueCountFrequency (%)
-61
100.0%
Math Symbol
ValueCountFrequency (%)
=27
100.0%
Connector Punctuation
ValueCountFrequency (%)
_14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2210
72.2%
Common850
 
27.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
t211
 
9.5%
e190
 
8.6%
s173
 
7.8%
o129
 
5.8%
h121
 
5.5%
p114
 
5.2%
r114
 
5.2%
a113
 
5.1%
i94
 
4.3%
w88
 
4.0%
Other values (39)863
39.0%
Common
ValueCountFrequency (%)
/246
28.9%
.140
16.5%
-61
 
7.2%
:58
 
6.8%
456
 
6.6%
154
 
6.4%
353
 
6.2%
233
 
3.9%
=27
 
3.2%
022
 
2.6%
Other values (9)100
11.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII3060
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/246
 
8.0%
t211
 
6.9%
e190
 
6.2%
s173
 
5.7%
.140
 
4.6%
o129
 
4.2%
h121
 
4.0%
p114
 
3.7%
r114
 
3.7%
a113
 
3.7%
Other values (58)1509
49.3%

_embedded.show.schedule.time
Categorical

HIGH CORRELATION

Distinct11
Distinct (%)18.3%
Missing0
Missing (%)0.0%
Memory size608.0 B
44 
06:00
10:00
 
3
17:00
 
1
18:55
 
1
Other values (6)

Length

Max length5
Median length0
Mean length1.333333333
Min length0

Characters and Unicode

Total characters80
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)13.3%

Sample

1st row
2nd row
3rd row10:00
4th row10:00
5th row10:00

Common Values

ValueCountFrequency (%)
44
73.3%
06:005
 
8.3%
10:003
 
5.0%
17:001
 
1.7%
18:551
 
1.7%
21:001
 
1.7%
14:001
 
1.7%
13:001
 
1.7%
22:301
 
1.7%
22:151
 
1.7%

Length

2022-09-05T21:42:26.166391image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
06:005
31.2%
10:003
18.8%
17:001
 
6.2%
18:551
 
6.2%
21:001
 
6.2%
14:001
 
6.2%
13:001
 
6.2%
22:301
 
6.2%
22:151
 
6.2%
20:001
 
6.2%

Most occurring characters

ValueCountFrequency (%)
036
45.0%
:16
20.0%
19
 
11.2%
26
 
7.5%
65
 
6.2%
53
 
3.8%
32
 
2.5%
71
 
1.2%
81
 
1.2%
41
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number64
80.0%
Other Punctuation16
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
036
56.2%
19
 
14.1%
26
 
9.4%
65
 
7.8%
53
 
4.7%
32
 
3.1%
71
 
1.6%
81
 
1.6%
41
 
1.6%
Other Punctuation
ValueCountFrequency (%)
:16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common80
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
036
45.0%
:16
20.0%
19
 
11.2%
26
 
7.5%
65
 
6.2%
53
 
3.8%
32
 
2.5%
71
 
1.2%
81
 
1.2%
41
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII80
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
036
45.0%
:16
20.0%
19
 
11.2%
26
 
7.5%
65
 
6.2%
53
 
3.8%
32
 
2.5%
71
 
1.2%
81
 
1.2%
41
 
1.2%

_embedded.show.schedule.days
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size608.0 B

_embedded.show.rating.average
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct6
Distinct (%)100.0%
Missing54
Missing (%)90.0%
Infinite0
Infinite (%)0.0%
Mean7.6
Minimum6.5
Maximum8.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size608.0 B
2022-09-05T21:42:26.233974image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum6.5
5-th percentile6.65
Q17.25
median7.85
Q38.075
95-th percentile8.175
Maximum8.2
Range1.7
Interquartile range (IQR)0.825

Descriptive statistics

Standard deviation0.6693280212
Coefficient of variation (CV)0.08806947648
Kurtosis-0.166015625
Mean7.6
Median Absolute Deviation (MAD)0.3
Skewness-1.050493895
Sum45.6
Variance0.448
MonotonicityNot monotonic
2022-09-05T21:42:26.309957image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
7.71
 
1.7%
81
 
1.7%
8.11
 
1.7%
8.21
 
1.7%
7.11
 
1.7%
6.51
 
1.7%
(Missing)54
90.0%
ValueCountFrequency (%)
6.51
1.7%
7.11
1.7%
7.71
1.7%
81
1.7%
8.11
1.7%
8.21
1.7%
ValueCountFrequency (%)
8.21
1.7%
8.11
1.7%
81
1.7%
7.71
1.7%
7.11
1.7%
6.51
1.7%

_embedded.show.weight
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct35
Distinct (%)58.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.65
Minimum2
Maximum93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size608.0 B
2022-09-05T21:42:26.403423image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q119.75
median35
Q359
95-th percentile87.05
Maximum93
Range91
Interquartile range (IQR)39.25

Descriptive statistics

Standard deviation27.25014383
Coefficient of variation (CV)0.6872671837
Kurtosis-0.9404378403
Mean39.65
Median Absolute Deviation (MAD)21
Skewness0.443907446
Sum2379
Variance742.570339
MonotonicityNot monotonic
2022-09-05T21:42:26.508200image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
277
 
11.7%
36
 
10.0%
395
 
8.3%
594
 
6.7%
143
 
5.0%
152
 
3.3%
822
 
3.3%
722
 
3.3%
222
 
3.3%
352
 
3.3%
Other values (25)25
41.7%
ValueCountFrequency (%)
21
 
1.7%
36
10.0%
41
 
1.7%
81
 
1.7%
143
5.0%
152
 
3.3%
191
 
1.7%
201
 
1.7%
211
 
1.7%
222
 
3.3%
ValueCountFrequency (%)
931
1.7%
911
1.7%
881
1.7%
871
1.7%
851
1.7%
822
3.3%
801
1.7%
781
1.7%
741
1.7%
722
3.3%

_embedded.show.network.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct7
Distinct (%)100.0%
Missing53
Missing (%)88.3%
Infinite0
Infinite (%)0.0%
Mean325.4285714
Minimum8
Maximum1320
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size608.0 B
2022-09-05T21:42:26.586098image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile32.9
Q1102.5
median132
Q3306.5
95-th percentile1036.2
Maximum1320
Range1312
Interquartile range (IQR)204

Descriptive statistics

Standard deviation454.0256443
Coefficient of variation (CV)1.395162208
Kurtosis5.528222363
Mean325.4285714
Median Absolute Deviation (MAD)107
Skewness2.297907025
Sum2278
Variance206139.2857
MonotonicityNot monotonic
2022-09-05T21:42:26.671097image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2391
 
1.7%
1141
 
1.7%
81
 
1.7%
13201
 
1.7%
3741
 
1.7%
1321
 
1.7%
911
 
1.7%
(Missing)53
88.3%
ValueCountFrequency (%)
81
1.7%
911
1.7%
1141
1.7%
1321
1.7%
2391
1.7%
3741
1.7%
13201
1.7%
ValueCountFrequency (%)
13201
1.7%
3741
1.7%
2391
1.7%
1321
1.7%
1141
1.7%
911
1.7%
81
1.7%

_embedded.show.network.name
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct7
Distinct (%)100.0%
Missing53
Missing (%)88.3%
Memory size608.0 B
Россия 1
ABC
HBO
UA:Перший
TV Globo
Other values (2)

Length

Max length9
Median length8
Mean length6.142857143
Min length3

Characters and Unicode

Total characters43
Distinct characters32
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)100.0%

Sample

1st rowРоссия 1
2nd rowABC
3rd rowHBO
4th rowUA:Перший
5th rowTV Globo

Common Values

ValueCountFrequency (%)
Россия 11
 
1.7%
ABC1
 
1.7%
HBO1
 
1.7%
UA:Перший1
 
1.7%
TV Globo1
 
1.7%
Tokyo MX1
 
1.7%
NRK11
 
1.7%
(Missing)53
88.3%

Length

2022-09-05T21:42:26.760525image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:42:26.861139image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
россия1
10.0%
11
10.0%
abc1
10.0%
hbo1
10.0%
ua:перший1
10.0%
tv1
10.0%
globo1
10.0%
tokyo1
10.0%
mx1
10.0%
nrk11
10.0%

Most occurring characters

ValueCountFrequency (%)
o4
 
9.3%
3
 
7.0%
с2
 
4.7%
и2
 
4.7%
12
 
4.7%
A2
 
4.7%
B2
 
4.7%
T2
 
4.7%
Р1
 
2.3%
k1
 
2.3%
Other values (22)22
51.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter19
44.2%
Lowercase Letter18
41.9%
Space Separator3
 
7.0%
Decimal Number2
 
4.7%
Other Punctuation1
 
2.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A2
 
10.5%
B2
 
10.5%
T2
 
10.5%
Р1
 
5.3%
G1
 
5.3%
N1
 
5.3%
M1
 
5.3%
X1
 
5.3%
R1
 
5.3%
V1
 
5.3%
Other values (6)6
31.6%
Lowercase Letter
ValueCountFrequency (%)
o4
22.2%
с2
11.1%
и2
11.1%
k1
 
5.6%
l1
 
5.6%
b1
 
5.6%
y1
 
5.6%
р1
 
5.6%
й1
 
5.6%
ш1
 
5.6%
Other values (3)3
16.7%
Space Separator
ValueCountFrequency (%)
3
100.0%
Decimal Number
ValueCountFrequency (%)
12
100.0%
Other Punctuation
ValueCountFrequency (%)
:1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin25
58.1%
Cyrillic12
27.9%
Common6
 
14.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o4
16.0%
A2
 
8.0%
B2
 
8.0%
T2
 
8.0%
k1
 
4.0%
G1
 
4.0%
l1
 
4.0%
b1
 
4.0%
N1
 
4.0%
y1
 
4.0%
Other values (9)9
36.0%
Cyrillic
ValueCountFrequency (%)
с2
16.7%
и2
16.7%
Р1
8.3%
р1
8.3%
й1
8.3%
ш1
8.3%
о1
8.3%
е1
8.3%
П1
8.3%
я1
8.3%
Common
ValueCountFrequency (%)
3
50.0%
12
33.3%
:1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII31
72.1%
Cyrillic12
 
27.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o4
 
12.9%
3
 
9.7%
12
 
6.5%
A2
 
6.5%
B2
 
6.5%
T2
 
6.5%
k1
 
3.2%
G1
 
3.2%
l1
 
3.2%
b1
 
3.2%
Other values (12)12
38.7%
Cyrillic
ValueCountFrequency (%)
с2
16.7%
и2
16.7%
Р1
8.3%
р1
8.3%
й1
8.3%
ш1
8.3%
о1
8.3%
е1
8.3%
П1
8.3%
я1
8.3%

_embedded.show.network.country.name
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct7
Distinct (%)100.0%
Missing53
Missing (%)88.3%
Memory size608.0 B
Russian Federation
Australia
United States
Ukraine
Brazil
Other values (2)

Length

Max length18
Median length9
Mean length9.142857143
Min length5

Characters and Unicode

Total characters64
Distinct characters25
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)100.0%

Sample

1st rowRussian Federation
2nd rowAustralia
3rd rowUnited States
4th rowUkraine
5th rowBrazil

Common Values

ValueCountFrequency (%)
Russian Federation1
 
1.7%
Australia1
 
1.7%
United States1
 
1.7%
Ukraine1
 
1.7%
Brazil1
 
1.7%
Japan1
 
1.7%
Norway1
 
1.7%
(Missing)53
88.3%

Length

2022-09-05T21:42:26.953409image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:42:27.053750image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
russian1
11.1%
federation1
11.1%
australia1
11.1%
united1
11.1%
states1
11.1%
ukraine1
11.1%
brazil1
11.1%
japan1
11.1%
norway1
11.1%

Most occurring characters

ValueCountFrequency (%)
a10
15.6%
i6
 
9.4%
t5
 
7.8%
n5
 
7.8%
e5
 
7.8%
r5
 
7.8%
s4
 
6.2%
o2
 
3.1%
U2
 
3.1%
l2
 
3.1%
Other values (15)18
28.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter53
82.8%
Uppercase Letter9
 
14.1%
Space Separator2
 
3.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a10
18.9%
i6
11.3%
t5
9.4%
n5
9.4%
e5
9.4%
r5
9.4%
s4
 
7.5%
o2
 
3.8%
l2
 
3.8%
u2
 
3.8%
Other values (6)7
13.2%
Uppercase Letter
ValueCountFrequency (%)
U2
22.2%
N1
11.1%
J1
11.1%
R1
11.1%
B1
11.1%
S1
11.1%
A1
11.1%
F1
11.1%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin62
96.9%
Common2
 
3.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a10
16.1%
i6
 
9.7%
t5
 
8.1%
n5
 
8.1%
e5
 
8.1%
r5
 
8.1%
s4
 
6.5%
o2
 
3.2%
U2
 
3.2%
l2
 
3.2%
Other values (14)16
25.8%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII64
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a10
15.6%
i6
 
9.4%
t5
 
7.8%
n5
 
7.8%
e5
 
7.8%
r5
 
7.8%
s4
 
6.2%
o2
 
3.1%
U2
 
3.1%
l2
 
3.1%
Other values (15)18
28.1%

_embedded.show.network.country.code
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct7
Distinct (%)100.0%
Missing53
Missing (%)88.3%
Memory size608.0 B
RU
AU
US
UA
BR
Other values (2)

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters14
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)100.0%

Sample

1st rowRU
2nd rowAU
3rd rowUS
4th rowUA
5th rowBR

Common Values

ValueCountFrequency (%)
RU1
 
1.7%
AU1
 
1.7%
US1
 
1.7%
UA1
 
1.7%
BR1
 
1.7%
JP1
 
1.7%
NO1
 
1.7%
(Missing)53
88.3%

Length

2022-09-05T21:42:27.138627image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:42:27.232640image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
ru1
14.3%
au1
14.3%
us1
14.3%
ua1
14.3%
br1
14.3%
jp1
14.3%
no1
14.3%

Most occurring characters

ValueCountFrequency (%)
U4
28.6%
R2
14.3%
A2
14.3%
S1
 
7.1%
B1
 
7.1%
J1
 
7.1%
P1
 
7.1%
N1
 
7.1%
O1
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter14
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U4
28.6%
R2
14.3%
A2
14.3%
S1
 
7.1%
B1
 
7.1%
J1
 
7.1%
P1
 
7.1%
N1
 
7.1%
O1
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
Latin14
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U4
28.6%
R2
14.3%
A2
14.3%
S1
 
7.1%
B1
 
7.1%
J1
 
7.1%
P1
 
7.1%
N1
 
7.1%
O1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U4
28.6%
R2
14.3%
A2
14.3%
S1
 
7.1%
B1
 
7.1%
J1
 
7.1%
P1
 
7.1%
N1
 
7.1%
O1
 
7.1%

_embedded.show.network.country.timezone
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct7
Distinct (%)100.0%
Missing53
Missing (%)88.3%
Memory size608.0 B
Asia/Kamchatka
Australia/Sydney
America/New_York
Europe/Zaporozhye
America/Noronha
Other values (2)

Length

Max length17
Median length15
Mean length14.14285714
Min length10

Characters and Unicode

Total characters99
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)100.0%

Sample

1st rowAsia/Kamchatka
2nd rowAustralia/Sydney
3rd rowAmerica/New_York
4th rowEurope/Zaporozhye
5th rowAmerica/Noronha

Common Values

ValueCountFrequency (%)
Asia/Kamchatka1
 
1.7%
Australia/Sydney1
 
1.7%
America/New_York1
 
1.7%
Europe/Zaporozhye1
 
1.7%
America/Noronha1
 
1.7%
Asia/Tokyo1
 
1.7%
Europe/Oslo1
 
1.7%
(Missing)53
88.3%

Length

2022-09-05T21:42:27.322536image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:42:27.423775image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
asia/kamchatka1
14.3%
australia/sydney1
14.3%
america/new_york1
14.3%
europe/zaporozhye1
14.3%
america/noronha1
14.3%
asia/tokyo1
14.3%
europe/oslo1
14.3%

Most occurring characters

ValueCountFrequency (%)
a11
 
11.1%
o10
 
10.1%
r8
 
8.1%
/7
 
7.1%
e7
 
7.1%
A5
 
5.1%
i5
 
5.1%
s4
 
4.0%
y4
 
4.0%
m3
 
3.0%
Other values (20)35
35.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter76
76.8%
Uppercase Letter15
 
15.2%
Other Punctuation7
 
7.1%
Connector Punctuation1
 
1.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a11
14.5%
o10
13.2%
r8
10.5%
e7
 
9.2%
i5
 
6.6%
s4
 
5.3%
y4
 
5.3%
m3
 
3.9%
u3
 
3.9%
h3
 
3.9%
Other values (9)18
23.7%
Uppercase Letter
ValueCountFrequency (%)
A5
33.3%
E2
 
13.3%
N2
 
13.3%
Y1
 
6.7%
K1
 
6.7%
S1
 
6.7%
Z1
 
6.7%
T1
 
6.7%
O1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
/7
100.0%
Connector Punctuation
ValueCountFrequency (%)
_1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin91
91.9%
Common8
 
8.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a11
 
12.1%
o10
 
11.0%
r8
 
8.8%
e7
 
7.7%
A5
 
5.5%
i5
 
5.5%
s4
 
4.4%
y4
 
4.4%
m3
 
3.3%
u3
 
3.3%
Other values (18)31
34.1%
Common
ValueCountFrequency (%)
/7
87.5%
_1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII99
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a11
 
11.1%
o10
 
10.1%
r8
 
8.1%
/7
 
7.1%
e7
 
7.1%
A5
 
5.1%
i5
 
5.1%
s4
 
4.0%
y4
 
4.0%
m3
 
3.0%
Other values (20)35
35.4%

_embedded.show.network.officialSite
Categorical

MISSING
UNIFORM

Distinct2
Distinct (%)100.0%
Missing58
Missing (%)96.7%
Memory size608.0 B
https://www.abc.net.au/
https://www.hbo.com/

Length

Max length23
Median length21.5
Mean length21.5
Min length20

Characters and Unicode

Total characters43
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowhttps://www.abc.net.au/
2nd rowhttps://www.hbo.com/

Common Values

ValueCountFrequency (%)
https://www.abc.net.au/1
 
1.7%
https://www.hbo.com/1
 
1.7%
(Missing)58
96.7%

Length

2022-09-05T21:42:27.514709image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:42:27.604034image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
https://www.abc.net.au1
50.0%
https://www.hbo.com1
50.0%

Most occurring characters

ValueCountFrequency (%)
/6
14.0%
w6
14.0%
t5
11.6%
.5
11.6%
h3
 
7.0%
p2
 
4.7%
s2
 
4.7%
:2
 
4.7%
a2
 
4.7%
b2
 
4.7%
Other values (6)8
18.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter30
69.8%
Other Punctuation13
30.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w6
20.0%
t5
16.7%
h3
10.0%
p2
 
6.7%
s2
 
6.7%
a2
 
6.7%
b2
 
6.7%
c2
 
6.7%
o2
 
6.7%
n1
 
3.3%
Other values (3)3
10.0%
Other Punctuation
ValueCountFrequency (%)
/6
46.2%
.5
38.5%
:2
 
15.4%

Most occurring scripts

ValueCountFrequency (%)
Latin30
69.8%
Common13
30.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
w6
20.0%
t5
16.7%
h3
10.0%
p2
 
6.7%
s2
 
6.7%
a2
 
6.7%
b2
 
6.7%
c2
 
6.7%
o2
 
6.7%
n1
 
3.3%
Other values (3)3
10.0%
Common
ValueCountFrequency (%)
/6
46.2%
.5
38.5%
:2
 
15.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII43
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/6
14.0%
w6
14.0%
t5
11.6%
.5
11.6%
h3
 
7.0%
p2
 
4.7%
s2
 
4.7%
:2
 
4.7%
a2
 
4.7%
b2
 
4.7%
Other values (6)8
18.6%

_embedded.show.webChannel
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing60
Missing (%)100.0%
Memory size608.0 B

_embedded.show.dvdCountry
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing60
Missing (%)100.0%
Memory size608.0 B

_embedded.show.externals.tvrage
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing60
Missing (%)100.0%
Memory size608.0 B

_embedded.show.externals.thetvdb
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct33
Distinct (%)76.7%
Missing17
Missing (%)28.3%
Infinite0
Infinite (%)0.0%
Mean363237.5116
Minimum244021
Maximum397247
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size608.0 B
2022-09-05T21:42:27.686805image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum244021
5-th percentile279146.6
Q1355725
median374464
Q3393038
95-th percentile397247
Maximum397247
Range153226
Interquartile range (IQR)37313

Descriptive statistics

Standard deviation39685.3828
Coefficient of variation (CV)0.1092546379
Kurtosis1.527860149
Mean363237.5116
Median Absolute Deviation (MAD)18963
Skewness-1.500658466
Sum15619213
Variance1574929608
MonotonicityNot monotonic
2022-09-05T21:42:27.788431image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
3972476
 
10.0%
3934274
 
6.7%
3682573
 
5.0%
3697981
 
1.7%
3936971
 
1.7%
3386311
 
1.7%
3744641
 
1.7%
2922471
 
1.7%
2440211
 
1.7%
3919761
 
1.7%
Other values (23)23
38.3%
(Missing)17
28.3%
ValueCountFrequency (%)
2440211
1.7%
2651931
1.7%
2776911
1.7%
2922471
1.7%
2941791
1.7%
3101021
1.7%
3103361
1.7%
3373361
1.7%
3386311
1.7%
3431611
1.7%
ValueCountFrequency (%)
3972476
10.0%
3936971
 
1.7%
3934274
6.7%
3926491
 
1.7%
3925981
 
1.7%
3919761
 
1.7%
3905861
 
1.7%
3904711
 
1.7%
3901301
 
1.7%
3861111
 
1.7%

_embedded.show.externals.imdb
Categorical

HIGH CORRELATION
MISSING

Distinct26
Distinct (%)83.9%
Missing29
Missing (%)48.3%
Memory size608.0 B
tt13819038
tt10727044
tt3886188
 
1
tt14369906
 
1
tt9471404
 
1
Other values (21)
21 

Length

Max length10
Median length10
Mean length9.677419355
Min length9

Characters and Unicode

Total characters300
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)77.4%

Sample

1st rowtt3886188
2nd rowtt9348700
3rd rowtt11492320
4th rowtt6940730
5th rowtt10727044

Common Values

ValueCountFrequency (%)
tt138190384
 
6.7%
tt107270443
 
5.0%
tt38861881
 
1.7%
tt143699061
 
1.7%
tt94714041
 
1.7%
tt102418121
 
1.7%
tt64686941
 
1.7%
tt03817531
 
1.7%
tt124579461
 
1.7%
tt132104701
 
1.7%
Other values (16)16
26.7%
(Missing)29
48.3%

Length

2022-09-05T21:42:27.882728image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tt138190384
 
12.9%
tt107270443
 
9.7%
tt93487001
 
3.2%
tt114923201
 
3.2%
tt69407301
 
3.2%
tt97643861
 
3.2%
tt126931481
 
3.2%
tt54238601
 
3.2%
tt76948741
 
3.2%
tt107010381
 
3.2%
Other values (16)16
51.6%

Most occurring characters

ValueCountFrequency (%)
t62
20.7%
138
12.7%
034
11.3%
331
10.3%
428
9.3%
826
8.7%
623
 
7.7%
920
 
6.7%
716
 
5.3%
216
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number238
79.3%
Lowercase Letter62
 
20.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
138
16.0%
034
14.3%
331
13.0%
428
11.8%
826
10.9%
623
9.7%
920
8.4%
716
6.7%
216
6.7%
56
 
2.5%
Lowercase Letter
ValueCountFrequency (%)
t62
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common238
79.3%
Latin62
 
20.7%

Most frequent character per script

Common
ValueCountFrequency (%)
138
16.0%
034
14.3%
331
13.0%
428
11.8%
826
10.9%
623
9.7%
920
8.4%
716
6.7%
216
6.7%
56
 
2.5%
Latin
ValueCountFrequency (%)
t62
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII300
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t62
20.7%
138
12.7%
034
11.3%
331
10.3%
428
9.3%
826
8.7%
623
 
7.7%
920
 
6.7%
716
 
5.3%
216
 
5.3%

_embedded.show.image.medium
Categorical

HIGH CORRELATION
MISSING

Distinct44
Distinct (%)78.6%
Missing4
Missing (%)6.7%
Memory size608.0 B
https://static.tvmaze.com/uploads/images/medium_portrait/308/770106.jpg
https://static.tvmaze.com/uploads/images/medium_portrait/291/729373.jpg
https://static.tvmaze.com/uploads/images/medium_portrait/288/721878.jpg
 
3
https://static.tvmaze.com/uploads/images/medium_portrait/383/958496.jpg
 
3
https://static.tvmaze.com/uploads/images/medium_portrait/164/410098.jpg
 
1
Other values (39)
39 

Length

Max length72
Median length71
Mean length71.03571429
Min length70

Characters and Unicode

Total characters3978
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)71.4%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_portrait/164/410098.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/255/639024.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/279/698895.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/286/715165.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/299/748854.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/308/770106.jpg6
 
10.0%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729373.jpg4
 
6.7%
https://static.tvmaze.com/uploads/images/medium_portrait/288/721878.jpg3
 
5.0%
https://static.tvmaze.com/uploads/images/medium_portrait/383/958496.jpg3
 
5.0%
https://static.tvmaze.com/uploads/images/medium_portrait/164/410098.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/medium_portrait/297/744219.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/medium_portrait/268/671692.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/medium_portrait/285/714414.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/medium_portrait/287/718562.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729040.jpg1
 
1.7%
Other values (34)34
56.7%
(Missing)4
 
6.7%

Length

2022-09-05T21:42:27.978397image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/308/770106.jpg6
 
10.7%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729373.jpg4
 
7.1%
https://static.tvmaze.com/uploads/images/medium_portrait/288/721878.jpg3
 
5.4%
https://static.tvmaze.com/uploads/images/medium_portrait/383/958496.jpg3
 
5.4%
https://static.tvmaze.com/uploads/images/medium_portrait/269/674781.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/213/533674.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/279/698895.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/286/715165.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/299/748854.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/96/240462.jpg1
 
1.8%
Other values (34)34
60.7%

Most occurring characters

ValueCountFrequency (%)
t392
 
9.9%
/392
 
9.9%
m280
 
7.0%
a280
 
7.0%
p224
 
5.6%
s224
 
5.6%
i224
 
5.6%
.168
 
4.2%
o168
 
4.2%
e168
 
4.2%
Other values (22)1458
36.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2800
70.4%
Other Punctuation616
 
15.5%
Decimal Number506
 
12.7%
Connector Punctuation56
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t392
14.0%
m280
10.0%
a280
10.0%
p224
 
8.0%
s224
 
8.0%
i224
 
8.0%
o168
 
6.0%
e168
 
6.0%
u112
 
4.0%
d112
 
4.0%
Other values (8)616
22.0%
Decimal Number
ValueCountFrequency (%)
266
13.0%
762
12.3%
160
11.9%
854
10.7%
953
10.5%
347
9.3%
047
9.3%
639
7.7%
539
7.7%
439
7.7%
Other Punctuation
ValueCountFrequency (%)
/392
63.6%
.168
27.3%
:56
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2800
70.4%
Common1178
29.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t392
14.0%
m280
10.0%
a280
10.0%
p224
 
8.0%
s224
 
8.0%
i224
 
8.0%
o168
 
6.0%
e168
 
6.0%
u112
 
4.0%
d112
 
4.0%
Other values (8)616
22.0%
Common
ValueCountFrequency (%)
/392
33.3%
.168
14.3%
266
 
5.6%
762
 
5.3%
160
 
5.1%
_56
 
4.8%
:56
 
4.8%
854
 
4.6%
953
 
4.5%
347
 
4.0%
Other values (4)164
13.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII3978
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t392
 
9.9%
/392
 
9.9%
m280
 
7.0%
a280
 
7.0%
p224
 
5.6%
s224
 
5.6%
i224
 
5.6%
.168
 
4.2%
o168
 
4.2%
e168
 
4.2%
Other values (22)1458
36.7%

_embedded.show.image.original
Categorical

HIGH CORRELATION
MISSING

Distinct44
Distinct (%)78.6%
Missing4
Missing (%)6.7%
Memory size608.0 B
https://static.tvmaze.com/uploads/images/original_untouched/308/770106.jpg
https://static.tvmaze.com/uploads/images/original_untouched/291/729373.jpg
https://static.tvmaze.com/uploads/images/original_untouched/288/721878.jpg
 
3
https://static.tvmaze.com/uploads/images/original_untouched/383/958496.jpg
 
3
https://static.tvmaze.com/uploads/images/original_untouched/164/410098.jpg
 
1
Other values (39)
39 

Length

Max length75
Median length74
Mean length74.03571429
Min length73

Characters and Unicode

Total characters4146
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)71.4%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/164/410098.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/255/639024.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/279/698895.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/286/715165.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/299/748854.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/308/770106.jpg6
 
10.0%
https://static.tvmaze.com/uploads/images/original_untouched/291/729373.jpg4
 
6.7%
https://static.tvmaze.com/uploads/images/original_untouched/288/721878.jpg3
 
5.0%
https://static.tvmaze.com/uploads/images/original_untouched/383/958496.jpg3
 
5.0%
https://static.tvmaze.com/uploads/images/original_untouched/164/410098.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/original_untouched/297/744219.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/original_untouched/268/671692.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/original_untouched/285/714414.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/original_untouched/287/718562.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/original_untouched/291/729040.jpg1
 
1.7%
Other values (34)34
56.7%
(Missing)4
 
6.7%

Length

2022-09-05T21:42:28.081491image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/308/770106.jpg6
 
10.7%
https://static.tvmaze.com/uploads/images/original_untouched/291/729373.jpg4
 
7.1%
https://static.tvmaze.com/uploads/images/original_untouched/288/721878.jpg3
 
5.4%
https://static.tvmaze.com/uploads/images/original_untouched/383/958496.jpg3
 
5.4%
https://static.tvmaze.com/uploads/images/original_untouched/269/674781.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/213/533674.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/279/698895.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/286/715165.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/299/748854.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/96/240462.jpg1
 
1.8%
Other values (34)34
60.7%

Most occurring characters

ValueCountFrequency (%)
/392
 
9.5%
t336
 
8.1%
a280
 
6.8%
s224
 
5.4%
i224
 
5.4%
o224
 
5.4%
p168
 
4.1%
c168
 
4.1%
.168
 
4.1%
g168
 
4.1%
Other values (23)1794
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2968
71.6%
Other Punctuation616
 
14.9%
Decimal Number506
 
12.2%
Connector Punctuation56
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t336
 
11.3%
a280
 
9.4%
s224
 
7.5%
i224
 
7.5%
o224
 
7.5%
p168
 
5.7%
c168
 
5.7%
g168
 
5.7%
m168
 
5.7%
e168
 
5.7%
Other values (9)840
28.3%
Decimal Number
ValueCountFrequency (%)
266
13.0%
762
12.3%
160
11.9%
854
10.7%
953
10.5%
347
9.3%
047
9.3%
639
7.7%
539
7.7%
439
7.7%
Other Punctuation
ValueCountFrequency (%)
/392
63.6%
.168
27.3%
:56
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2968
71.6%
Common1178
 
28.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t336
 
11.3%
a280
 
9.4%
s224
 
7.5%
i224
 
7.5%
o224
 
7.5%
p168
 
5.7%
c168
 
5.7%
g168
 
5.7%
m168
 
5.7%
e168
 
5.7%
Other values (9)840
28.3%
Common
ValueCountFrequency (%)
/392
33.3%
.168
14.3%
266
 
5.6%
762
 
5.3%
160
 
5.1%
:56
 
4.8%
_56
 
4.8%
854
 
4.6%
953
 
4.5%
347
 
4.0%
Other values (4)164
13.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII4146
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/392
 
9.5%
t336
 
8.1%
a280
 
6.8%
s224
 
5.4%
i224
 
5.4%
o224
 
5.4%
p168
 
4.1%
c168
 
4.1%
.168
 
4.1%
g168
 
4.1%
Other values (23)1794
43.3%

_embedded.show.summary
Categorical

HIGH CORRELATION
MISSING

Distinct43
Distinct (%)78.2%
Missing5
Missing (%)8.3%
Memory size608.0 B
<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>
<p>A thrilling true crime series following a young mother facing up to 99 years in prison for murder. As the case unravels over 5 years, those closest to her search for the truth.</p>
<p>A relationship drama about two young people who fall in love at a difficult time in life. In the series, we meet Anders and Mio who, after a one night stand, find out that they are pregnant.</p>
 
3
<p>Solan, Ludvig and Reodor were regular companions. Here is the story of the artist who hit the Norwegian people's soul and the hearts of both children and adults.</p>
 
3
<p>Once they were the coolest guys in school. Ten years later, they are still partying as if they were carefree teenagers. Now it's high time for daddy's boys to grow up.</p>
 
1
Other values (38)
38 

Length

Max length913
Median length417
Mean length391.3454545
Min length108

Characters and Unicode

Total characters21524
Distinct characters102
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)70.9%

Sample

1st row<p>Zero was mankind's first real superhero. Under his watch, countless other superheros appeared and followed in his footsteps. However, after 5 years of war, Zero disappeared without a trace.<br /><br />(Source: zeroscans)</p>
2nd row<p>One day, an unexplained RR virus appeared on the earth, drawing the world into disaster. Infected animals mutated into terrible monsters, invaded massively, and humans built walls around the destruction and established the base city as the last bastion for humans. The suffering that mankind has experienced during this period of time is known as the "Great Nirvana Period." Not only that, Luo Feng not only carried the burden of supporting the family but also to protect the human homeland, for the better survival and development of mankind, together with other justice warriors, to join hands against the fierce monsters. Under the desperate situation of the end, can Luo Feng and other warriors repel monsters and successfully protect the human world?</p>
3rd row<p>The protagonist Qin Chen, who was originally the top genius in the military domain, was conspired by the people to fall into the death canyon in the forbidden land of the mainland. Qin Chen, who was inevitably dead, unexpectedly triggered the power of the mysterious ancient sword.<br /><br />Three hundred years later, in a remote part of the Tianwu mainland, a boy of the same name accidentally inherited Qin Chen's will. As the beloved grandson of King Dingwu of the Daqi National Army, due to the birth father's birth, the mother and son were treated coldly in Dingwu's palace and lived together. In order to rewrite the myth of the strong man in hope of the sun, and to protect everything he loves, Qin Chen resolutely took up the responsibility of maintaining the five kingdoms of the world and set foot on the road of martial arts again.</p>
4th row<p><b>New Japan Pro Wrestling</b> (NJPW) is the largest professional wrestling promotion in Japan and the second largest promotion in the world.</p>
5th row<p>In the twenty-first century, gods and demons can no longer maintain balance due to the rapid development of human society. In an effort to restore proper order, the gods began to take care of saving the world, for which they sent a group of gods and monsters to the world of people, who must find there the " key " to salvation. Su moting is a girl with the personality of "demon child". When her parents asked her to leave home so that she could become independent and independent, she met the beautiful and charming God of Tianjin and the mysterious demon cat. So begins a new turbulent round of su moting's life.</p><p><br /> </p>

Common Values

ValueCountFrequency (%)
<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>6
 
10.0%
<p>A thrilling true crime series following a young mother facing up to 99 years in prison for murder. As the case unravels over 5 years, those closest to her search for the truth.</p>4
 
6.7%
<p>A relationship drama about two young people who fall in love at a difficult time in life. In the series, we meet Anders and Mio who, after a one night stand, find out that they are pregnant.</p>3
 
5.0%
<p>Solan, Ludvig and Reodor were regular companions. Here is the story of the artist who hit the Norwegian people's soul and the hearts of both children and adults.</p>3
 
5.0%
<p>Once they were the coolest guys in school. Ten years later, they are still partying as if they were carefree teenagers. Now it's high time for daddy's boys to grow up.</p>1
 
1.7%
<p><b>The George Lucas Talk Show</b>, a long-running cult talk show hosted by Connor Ratliff, as George Lucas, his sidekick Watto (Griffin Newman), and his producer Patrick Cotnoir. They interview guests in a panel format weekly on PlanetScum.</p>1
 
1.7%
<p>A show of intellectual satire. The show discusses national and foreign issues in a witty and biting way, and once a month - a topic prepared in detail by the screenwriters. Since the beginning of the fifth season, three hosts have shared the main wheel: Andrius Tapinas, Ignas Grinevičius, and Irma Bogdanovičiūtė.</p>1
 
1.7%
<p>Farah and Shadi are left to deal with the consequences of their son's kidnapping. Between war and peace, Majed and Dalal rediscover their relationship.</p>1
 
1.7%
<p>In a post-apocalyptic world, alone in a bunker, Alice tries to communicate with the outside through the radio.</p>1
 
1.7%
<p>Our crew is recruited by T.O.R.C.H for what seems like a simple mission of delivering water to a far off planet. They get way more than they bargained for along the way, and maybe learn more about themselves during their adventures. Storyteller Eugenio Vargas leads cast members Krystina Arielle, DeejayKnight, Tanya DePass and Michael Sinclair II on a 12 session run around their galaxy and their home planet.</p>1
 
1.7%
Other values (33)33
55.0%
(Missing)5
 
8.3%

Length

2022-09-05T21:42:28.206682image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the247
 
6.9%
and132
 
3.7%
of103
 
2.9%
to100
 
2.8%
a91
 
2.5%
in85
 
2.4%
his39
 
1.1%
who38
 
1.1%
is32
 
0.9%
with31
 
0.9%
Other values (1195)2687
75.0%

Most occurring characters

ValueCountFrequency (%)
3520
16.4%
e1966
 
9.1%
t1475
 
6.9%
a1317
 
6.1%
n1244
 
5.8%
o1227
 
5.7%
i1218
 
5.7%
r1096
 
5.1%
s1022
 
4.7%
h895
 
4.2%
Other values (92)6544
30.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter16218
75.3%
Space Separator3531
 
16.4%
Uppercase Letter670
 
3.1%
Other Punctuation633
 
2.9%
Math Symbol364
 
1.7%
Dash Punctuation41
 
0.2%
Decimal Number41
 
0.2%
Other Letter8
 
< 0.1%
Open Punctuation7
 
< 0.1%
Close Punctuation7
 
< 0.1%
Other values (3)4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e1966
12.1%
t1475
 
9.1%
a1317
 
8.1%
n1244
 
7.7%
o1227
 
7.6%
i1218
 
7.5%
r1096
 
6.8%
s1022
 
6.3%
h895
 
5.5%
d607
 
3.7%
Other values (24)4151
25.6%
Uppercase Letter
ValueCountFrequency (%)
T73
 
10.9%
S64
 
9.6%
J53
 
7.9%
A44
 
6.6%
M37
 
5.5%
X36
 
5.4%
H33
 
4.9%
I27
 
4.0%
L26
 
3.9%
F24
 
3.6%
Other values (17)253
37.8%
Other Punctuation
ValueCountFrequency (%)
,212
33.5%
.186
29.4%
/97
15.3%
"49
 
7.7%
'46
 
7.3%
:24
 
3.8%
!12
 
1.9%
?5
 
0.8%
@1
 
0.2%
#1
 
0.2%
Decimal Number
ValueCountFrequency (%)
911
26.8%
08
19.5%
16
14.6%
25
12.2%
55
12.2%
42
 
4.9%
82
 
4.9%
72
 
4.9%
Other Letter
ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
Dash Punctuation
ValueCountFrequency (%)
-31
75.6%
8
 
19.5%
2
 
4.9%
Space Separator
ValueCountFrequency (%)
3520
99.7%
 11
 
0.3%
Math Symbol
ValueCountFrequency (%)
>182
50.0%
<182
50.0%
Open Punctuation
ValueCountFrequency (%)
(6
85.7%
[1
 
14.3%
Close Punctuation
ValueCountFrequency (%)
)6
85.7%
]1
 
14.3%
Currency Symbol
ValueCountFrequency (%)
$1
50.0%
1
50.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%
Modifier Letter
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin16888
78.5%
Common4628
 
21.5%
Han4
 
< 0.1%
Katakana4
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e1966
11.6%
t1475
 
8.7%
a1317
 
7.8%
n1244
 
7.4%
o1227
 
7.3%
i1218
 
7.2%
r1096
 
6.5%
s1022
 
6.1%
h895
 
5.3%
d607
 
3.6%
Other values (51)4821
28.5%
Common
ValueCountFrequency (%)
3520
76.1%
,212
 
4.6%
.186
 
4.0%
>182
 
3.9%
<182
 
3.9%
/97
 
2.1%
"49
 
1.1%
'46
 
1.0%
-31
 
0.7%
:24
 
0.5%
Other values (23)99
 
2.1%
Han
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Katakana
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII21476
99.8%
None27
 
0.1%
Punctuation10
 
< 0.1%
Katakana5
 
< 0.1%
CJK4
 
< 0.1%
Dingbats1
 
< 0.1%
Currency Symbols1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3520
16.4%
e1966
 
9.2%
t1475
 
6.9%
a1317
 
6.1%
n1244
 
5.8%
o1227
 
5.7%
i1218
 
5.7%
r1096
 
5.1%
s1022
 
4.8%
h895
 
4.2%
Other values (69)6496
30.2%
None
ValueCountFrequency (%)
 11
40.7%
ä3
 
11.1%
å2
 
7.4%
Å2
 
7.4%
ö2
 
7.4%
é2
 
7.4%
č2
 
7.4%
ā1
 
3.7%
ė1
 
3.7%
ū1
 
3.7%
Punctuation
ValueCountFrequency (%)
8
80.0%
2
 
20.0%
CJK
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Dingbats
ValueCountFrequency (%)
1
100.0%
Katakana
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Currency Symbols
ValueCountFrequency (%)
1
100.0%

_embedded.show.updated
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct48
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1635863703
Minimum1603467037
Maximum1662305316
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size608.0 B
2022-09-05T21:42:28.327467image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1603467037
5-th percentile1609075962
Q11618466682
median1633449182
Q31653582714
95-th percentile1661963157
Maximum1662305316
Range58838279
Interquartile range (IQR)35116032

Descriptive statistics

Standard deviation18668358.77
Coefficient of variation (CV)0.01141192799
Kurtosis-1.4789209
Mean1635863703
Median Absolute Deviation (MAD)15927855.5
Skewness-0.04676044422
Sum9.815182216 × 1010
Variance3.485076192 × 1014
MonotonicityNot monotonic
2022-09-05T21:42:28.448167image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
16184666826
 
10.0%
16270500894
 
6.7%
16535827143
 
5.0%
16090759623
 
5.0%
16597047501
 
1.7%
16120609221
 
1.7%
16532523561
 
1.7%
16182435821
 
1.7%
16612645191
 
1.7%
16450396161
 
1.7%
Other values (38)38
63.3%
ValueCountFrequency (%)
16034670371
 
1.7%
16085040201
 
1.7%
16090759623
5.0%
16096167881
 
1.7%
16110394971
 
1.7%
16114368421
 
1.7%
16120609221
 
1.7%
16140384281
 
1.7%
16182435821
 
1.7%
16184666826
10.0%
ValueCountFrequency (%)
16623053161
1.7%
16622069171
1.7%
16620258751
1.7%
16619598561
1.7%
16612645191
1.7%
16612547171
1.7%
16611076721
1.7%
16610060421
1.7%
16597047501
1.7%
16554701641
1.7%

_embedded.show._links.self.href
Categorical

HIGH CORRELATION

Distinct48
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Memory size608.0 B
https://api.tvmaze.com/shows/54762
https://api.tvmaze.com/shows/52772
 
4
https://api.tvmaze.com/shows/44057
 
3
https://api.tvmaze.com/shows/52423
 
3
https://api.tvmaze.com/shows/38199
 
1
Other values (43)
43 

Length

Max length34
Median length34
Mean length34
Min length34

Characters and Unicode

Total characters2040
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)73.3%

Sample

1st rowhttps://api.tvmaze.com/shows/38199
2nd rowhttps://api.tvmaze.com/shows/47865
3rd rowhttps://api.tvmaze.com/shows/51471
4th rowhttps://api.tvmaze.com/shows/52178
5th rowhttps://api.tvmaze.com/shows/54033

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/shows/547626
 
10.0%
https://api.tvmaze.com/shows/527724
 
6.7%
https://api.tvmaze.com/shows/440573
 
5.0%
https://api.tvmaze.com/shows/524233
 
5.0%
https://api.tvmaze.com/shows/381991
 
1.7%
https://api.tvmaze.com/shows/521481
 
1.7%
https://api.tvmaze.com/shows/523031
 
1.7%
https://api.tvmaze.com/shows/527371
 
1.7%
https://api.tvmaze.com/shows/528581
 
1.7%
https://api.tvmaze.com/shows/533381
 
1.7%
Other values (38)38
63.3%

Length

2022-09-05T21:42:28.544692image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/shows/547626
 
10.0%
https://api.tvmaze.com/shows/527724
 
6.7%
https://api.tvmaze.com/shows/440573
 
5.0%
https://api.tvmaze.com/shows/524233
 
5.0%
https://api.tvmaze.com/shows/349011
 
1.7%
https://api.tvmaze.com/shows/478651
 
1.7%
https://api.tvmaze.com/shows/514711
 
1.7%
https://api.tvmaze.com/shows/521781
 
1.7%
https://api.tvmaze.com/shows/540331
 
1.7%
https://api.tvmaze.com/shows/249631
 
1.7%
Other values (38)38
63.3%

Most occurring characters

ValueCountFrequency (%)
/240
 
11.8%
s180
 
8.8%
t180
 
8.8%
h120
 
5.9%
p120
 
5.9%
a120
 
5.9%
o120
 
5.9%
.120
 
5.9%
m120
 
5.9%
e60
 
2.9%
Other values (16)660
32.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1320
64.7%
Other Punctuation420
 
20.6%
Decimal Number300
 
14.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s180
13.6%
t180
13.6%
h120
9.1%
p120
9.1%
a120
9.1%
o120
9.1%
m120
9.1%
e60
 
4.5%
w60
 
4.5%
c60
 
4.5%
Other values (3)180
13.6%
Decimal Number
ValueCountFrequency (%)
546
15.3%
445
15.0%
245
15.0%
335
11.7%
732
10.7%
926
8.7%
120
6.7%
619
6.3%
817
 
5.7%
015
 
5.0%
Other Punctuation
ValueCountFrequency (%)
/240
57.1%
.120
28.6%
:60
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin1320
64.7%
Common720
35.3%

Most frequent character per script

Common
ValueCountFrequency (%)
/240
33.3%
.120
16.7%
:60
 
8.3%
546
 
6.4%
445
 
6.2%
245
 
6.2%
335
 
4.9%
732
 
4.4%
926
 
3.6%
120
 
2.8%
Other values (3)51
 
7.1%
Latin
ValueCountFrequency (%)
s180
13.6%
t180
13.6%
h120
9.1%
p120
9.1%
a120
9.1%
o120
9.1%
m120
9.1%
e60
 
4.5%
w60
 
4.5%
c60
 
4.5%
Other values (3)180
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII2040
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/240
 
11.8%
s180
 
8.8%
t180
 
8.8%
h120
 
5.9%
p120
 
5.9%
a120
 
5.9%
o120
 
5.9%
.120
 
5.9%
m120
 
5.9%
e60
 
2.9%
Other values (16)660
32.4%
Distinct48
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Memory size608.0 B
https://api.tvmaze.com/episodes/2071494
https://api.tvmaze.com/episodes/1998365
 
4
https://api.tvmaze.com/episodes/2333793
 
3
https://api.tvmaze.com/episodes/1985429
 
3
https://api.tvmaze.com/episodes/2370911
 
1
Other values (43)
43 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters2340
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)73.3%

Sample

1st rowhttps://api.tvmaze.com/episodes/2370911
2nd rowhttps://api.tvmaze.com/episodes/2348600
3rd rowhttps://api.tvmaze.com/episodes/1956341
4th rowhttps://api.tvmaze.com/episodes/2259040
5th rowhttps://api.tvmaze.com/episodes/2309442

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/20714946
 
10.0%
https://api.tvmaze.com/episodes/19983654
 
6.7%
https://api.tvmaze.com/episodes/23337933
 
5.0%
https://api.tvmaze.com/episodes/19854293
 
5.0%
https://api.tvmaze.com/episodes/23709111
 
1.7%
https://api.tvmaze.com/episodes/19860811
 
1.7%
https://api.tvmaze.com/episodes/23321741
 
1.7%
https://api.tvmaze.com/episodes/20564141
 
1.7%
https://api.tvmaze.com/episodes/23780191
 
1.7%
https://api.tvmaze.com/episodes/22774201
 
1.7%
Other values (38)38
63.3%

Length

2022-09-05T21:42:28.630960image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/20714946
 
10.0%
https://api.tvmaze.com/episodes/19983654
 
6.7%
https://api.tvmaze.com/episodes/23337933
 
5.0%
https://api.tvmaze.com/episodes/19854293
 
5.0%
https://api.tvmaze.com/episodes/23797961
 
1.7%
https://api.tvmaze.com/episodes/23486001
 
1.7%
https://api.tvmaze.com/episodes/19563411
 
1.7%
https://api.tvmaze.com/episodes/22590401
 
1.7%
https://api.tvmaze.com/episodes/23094421
 
1.7%
https://api.tvmaze.com/episodes/23767281
 
1.7%
Other values (38)38
63.3%

Most occurring characters

ValueCountFrequency (%)
/240
 
10.3%
t180
 
7.7%
p180
 
7.7%
s180
 
7.7%
e180
 
7.7%
a120
 
5.1%
i120
 
5.1%
.120
 
5.1%
m120
 
5.1%
o120
 
5.1%
Other values (16)780
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1500
64.1%
Other Punctuation420
 
17.9%
Decimal Number420
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t180
12.0%
p180
12.0%
s180
12.0%
e180
12.0%
a120
8.0%
i120
8.0%
m120
8.0%
o120
8.0%
h60
 
4.0%
d60
 
4.0%
Other values (3)180
12.0%
Decimal Number
ValueCountFrequency (%)
267
16.0%
152
12.4%
951
12.1%
347
11.2%
742
10.0%
437
8.8%
635
8.3%
831
7.4%
030
7.1%
528
6.7%
Other Punctuation
ValueCountFrequency (%)
/240
57.1%
.120
28.6%
:60
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin1500
64.1%
Common840
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/240
28.6%
.120
14.3%
267
 
8.0%
:60
 
7.1%
152
 
6.2%
951
 
6.1%
347
 
5.6%
742
 
5.0%
437
 
4.4%
635
 
4.2%
Other values (3)89
 
10.6%
Latin
ValueCountFrequency (%)
t180
12.0%
p180
12.0%
s180
12.0%
e180
12.0%
a120
8.0%
i120
8.0%
m120
8.0%
o120
8.0%
h60
 
4.0%
d60
 
4.0%
Other values (3)180
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2340
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/240
 
10.3%
t180
 
7.7%
p180
 
7.7%
s180
 
7.7%
e180
 
7.7%
a120
 
5.1%
i120
 
5.1%
.120
 
5.1%
m120
 
5.1%
o120
 
5.1%
Other values (16)780
33.3%

image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing60
Missing (%)100.0%
Memory size608.0 B

_embedded.show.network
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing60
Missing (%)100.0%
Memory size608.0 B

_embedded.show.webChannel.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct27
Distinct (%)47.4%
Missing3
Missing (%)5.0%
Infinite0
Infinite (%)0.0%
Mean173.3859649
Minimum15
Maximum443
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size608.0 B
2022-09-05T21:42:28.722793image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile21
Q171
median118
Q3304
95-th percentile379
Maximum443
Range428
Interquartile range (IQR)233

Descriptive statistics

Standard deviation129.4301735
Coefficient of variation (CV)0.7464858734
Kurtosis-1.244083791
Mean173.3859649
Median Absolute Deviation (MAD)97
Skewness0.3728735336
Sum9883
Variance16752.1698
MonotonicityNot monotonic
2022-09-05T21:42:28.818473image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
2110
16.7%
1186
 
10.0%
2386
 
10.0%
3275
 
8.3%
714
 
6.7%
1043
 
5.0%
3772
 
3.3%
3792
 
3.3%
2651
 
1.7%
3881
 
1.7%
Other values (17)17
28.3%
(Missing)3
 
5.0%
ValueCountFrequency (%)
151
 
1.7%
2110
16.7%
221
 
1.7%
321
 
1.7%
511
 
1.7%
714
 
6.7%
1031
 
1.7%
1043
 
5.0%
1071
 
1.7%
1186
10.0%
ValueCountFrequency (%)
4431
 
1.7%
3881
 
1.7%
3792
 
3.3%
3772
 
3.3%
3311
 
1.7%
3275
8.3%
3211
 
1.7%
3151
 
1.7%
3041
 
1.7%
2941
 
1.7%

_embedded.show.webChannel.name
Categorical

HIGH CORRELATION
MISSING

Distinct27
Distinct (%)47.4%
Missing3
Missing (%)5.0%
Memory size608.0 B
YouTube
10 
Youku
NRK TV
TV 2 Play
BBC Three
Other values (22)
26 

Length

Max length19
Median length13
Mean length8.228070175
Min length4

Characters and Unicode

Total characters469
Distinct characters47
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)33.3%

Sample

1st rowYouTube
2nd rowTencent QQ
3rd rowTencent QQ
4th rowTencent QQ
5th rowNJPW World

Common Values

ValueCountFrequency (%)
YouTube10
16.7%
Youku6
 
10.0%
NRK TV6
 
10.0%
TV 2 Play5
 
8.3%
BBC Three4
 
6.7%
Tencent QQ3
 
5.0%
ATRESplayer PREMIUM2
 
3.3%
Shahid2
 
3.3%
ESPN+1
 
1.7%
VidAngel1
 
1.7%
Other values (17)17
28.3%
(Missing)3
 
5.0%

Length

2022-09-05T21:42:28.914674image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tv12
 
13.2%
youtube10
 
11.0%
nrk6
 
6.6%
play6
 
6.6%
youku6
 
6.6%
25
 
5.5%
bbc4
 
4.4%
three4
 
4.4%
tencent3
 
3.3%
qq3
 
3.3%
Other values (29)32
35.2%

Most occurring characters

ValueCountFrequency (%)
e37
 
7.9%
u35
 
7.5%
34
 
7.2%
T33
 
7.0%
o30
 
6.4%
a20
 
4.3%
l17
 
3.6%
Y16
 
3.4%
V16
 
3.4%
i13
 
2.8%
Other values (37)218
46.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter263
56.1%
Uppercase Letter164
35.0%
Space Separator34
 
7.2%
Decimal Number5
 
1.1%
Math Symbol3
 
0.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T33
20.1%
Y16
9.8%
V16
9.8%
P12
 
7.3%
R11
 
6.7%
B11
 
6.7%
N9
 
5.5%
S8
 
4.9%
K7
 
4.3%
Q6
 
3.7%
Other values (13)35
21.3%
Lowercase Letter
ValueCountFrequency (%)
e37
14.1%
u35
13.3%
o30
11.4%
a20
 
7.6%
l17
 
6.5%
i13
 
4.9%
r13
 
4.9%
t12
 
4.6%
b12
 
4.6%
y11
 
4.2%
Other values (11)63
24.0%
Space Separator
ValueCountFrequency (%)
34
100.0%
Decimal Number
ValueCountFrequency (%)
25
100.0%
Math Symbol
ValueCountFrequency (%)
+3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin427
91.0%
Common42
 
9.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e37
 
8.7%
u35
 
8.2%
T33
 
7.7%
o30
 
7.0%
a20
 
4.7%
l17
 
4.0%
Y16
 
3.7%
V16
 
3.7%
i13
 
3.0%
r13
 
3.0%
Other values (34)197
46.1%
Common
ValueCountFrequency (%)
34
81.0%
25
 
11.9%
+3
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII469
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e37
 
7.9%
u35
 
7.5%
34
 
7.2%
T33
 
7.0%
o30
 
6.4%
a20
 
4.3%
l17
 
3.6%
Y16
 
3.4%
V16
 
3.4%
i13
 
2.8%
Other values (37)218
46.5%

_embedded.show.webChannel.country
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing60
Missing (%)100.0%
Memory size608.0 B

_embedded.show.webChannel.officialSite
Categorical

HIGH CORRELATION
MISSING

Distinct7
Distinct (%)33.3%
Missing39
Missing (%)65.0%
Memory size608.0 B
https://www.youtube.com
10 
https://www.bbc.co.uk/bbcthree
https://v.qq.com/
https://tv.kakao.com/top
 
1
https://viaplay.com
 
1
Other values (2)

Length

Max length30
Median length24
Mean length24
Min length17

Characters and Unicode

Total characters504
Distinct characters24
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)19.0%

Sample

1st rowhttps://www.youtube.com
2nd rowhttps://v.qq.com/
3rd rowhttps://v.qq.com/
4th rowhttps://v.qq.com/
5th rowhttps://tv.kakao.com/top

Common Values

ValueCountFrequency (%)
https://www.youtube.com10
 
16.7%
https://www.bbc.co.uk/bbcthree4
 
6.7%
https://v.qq.com/3
 
5.0%
https://tv.kakao.com/top1
 
1.7%
https://viaplay.com1
 
1.7%
https://www.discoveryplus.com/1
 
1.7%
https://www.paramountplus.com/1
 
1.7%
(Missing)39
65.0%

Length

2022-09-05T21:42:29.008402image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:42:29.117667image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
https://www.youtube.com10
47.6%
https://www.bbc.co.uk/bbcthree4
 
19.0%
https://v.qq.com3
 
14.3%
https://tv.kakao.com/top1
 
4.8%
https://viaplay.com1
 
4.8%
https://www.discoveryplus.com1
 
4.8%
https://www.paramountplus.com1
 
4.8%

Most occurring characters

ValueCountFrequency (%)
t59
11.7%
/52
 
10.3%
w48
 
9.5%
.45
 
8.9%
o35
 
6.9%
c30
 
6.0%
u27
 
5.4%
p26
 
5.2%
b26
 
5.2%
h25
 
5.0%
Other values (14)131
26.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter386
76.6%
Other Punctuation118
 
23.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t59
15.3%
w48
12.4%
o35
9.1%
c30
7.8%
u27
7.0%
p26
 
6.7%
b26
 
6.7%
h25
 
6.5%
s24
 
6.2%
e19
 
4.9%
Other values (11)67
17.4%
Other Punctuation
ValueCountFrequency (%)
/52
44.1%
.45
38.1%
:21
17.8%

Most occurring scripts

ValueCountFrequency (%)
Latin386
76.6%
Common118
 
23.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t59
15.3%
w48
12.4%
o35
9.1%
c30
7.8%
u27
7.0%
p26
 
6.7%
b26
 
6.7%
h25
 
6.5%
s24
 
6.2%
e19
 
4.9%
Other values (11)67
17.4%
Common
ValueCountFrequency (%)
/52
44.1%
.45
38.1%
:21
17.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII504
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t59
11.7%
/52
 
10.3%
w48
 
9.5%
.45
 
8.9%
o35
 
6.9%
c30
 
6.0%
u27
 
5.4%
p26
 
5.2%
b26
 
5.2%
h25
 
5.0%
Other values (14)131
26.0%

_embedded.show.webChannel.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct10
Distinct (%)26.3%
Missing22
Missing (%)36.7%
Memory size608.0 B
Norway
11 
China
10 
United States
United Kingdom
Spain
Other values (5)

Length

Max length18
Median length14
Mean length8
Min length5

Characters and Unicode

Total characters304
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)13.2%

Sample

1st rowChina
2nd rowChina
3rd rowChina
4th rowJapan
5th rowChina

Common Values

ValueCountFrequency (%)
Norway11
18.3%
China10
16.7%
United States6
 
10.0%
United Kingdom4
 
6.7%
Spain2
 
3.3%
Japan1
 
1.7%
Korea, Republic of1
 
1.7%
Australia1
 
1.7%
Sweden1
 
1.7%
Brazil1
 
1.7%
(Missing)22
36.7%

Length

2022-09-05T21:42:29.217026image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:42:29.330930image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
norway11
22.0%
china10
20.0%
united10
20.0%
states6
12.0%
kingdom4
 
8.0%
spain2
 
4.0%
japan1
 
2.0%
korea1
 
2.0%
republic1
 
2.0%
of1
 
2.0%
Other values (3)3
 
6.0%

Most occurring characters

ValueCountFrequency (%)
a35
 
11.5%
i29
 
9.5%
n28
 
9.2%
t23
 
7.6%
e20
 
6.6%
o17
 
5.6%
d15
 
4.9%
r14
 
4.6%
w12
 
3.9%
12
 
3.9%
Other values (22)99
32.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter242
79.6%
Uppercase Letter49
 
16.1%
Space Separator12
 
3.9%
Other Punctuation1
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a35
14.5%
i29
12.0%
n28
11.6%
t23
9.5%
e20
8.3%
o17
7.0%
d15
 
6.2%
r14
 
5.8%
w12
 
5.0%
y11
 
4.5%
Other values (11)38
15.7%
Uppercase Letter
ValueCountFrequency (%)
N11
22.4%
C10
20.4%
U10
20.4%
S9
18.4%
K5
10.2%
J1
 
2.0%
R1
 
2.0%
A1
 
2.0%
B1
 
2.0%
Space Separator
ValueCountFrequency (%)
12
100.0%
Other Punctuation
ValueCountFrequency (%)
,1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin291
95.7%
Common13
 
4.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a35
12.0%
i29
 
10.0%
n28
 
9.6%
t23
 
7.9%
e20
 
6.9%
o17
 
5.8%
d15
 
5.2%
r14
 
4.8%
w12
 
4.1%
N11
 
3.8%
Other values (20)87
29.9%
Common
ValueCountFrequency (%)
12
92.3%
,1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII304
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a35
 
11.5%
i29
 
9.5%
n28
 
9.2%
t23
 
7.6%
e20
 
6.6%
o17
 
5.6%
d15
 
4.9%
r14
 
4.6%
w12
 
3.9%
12
 
3.9%
Other values (22)99
32.6%

_embedded.show.webChannel.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct10
Distinct (%)26.3%
Missing22
Missing (%)36.7%
Memory size608.0 B
NO
11 
CN
10 
US
GB
ES
Other values (5)

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters76
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)13.2%

Sample

1st rowCN
2nd rowCN
3rd rowCN
4th rowJP
5th rowCN

Common Values

ValueCountFrequency (%)
NO11
18.3%
CN10
16.7%
US6
 
10.0%
GB4
 
6.7%
ES2
 
3.3%
JP1
 
1.7%
KR1
 
1.7%
AU1
 
1.7%
SE1
 
1.7%
BR1
 
1.7%
(Missing)22
36.7%

Length

2022-09-05T21:42:29.428122image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:42:29.537185image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
no11
28.9%
cn10
26.3%
us6
15.8%
gb4
 
10.5%
es2
 
5.3%
jp1
 
2.6%
kr1
 
2.6%
au1
 
2.6%
se1
 
2.6%
br1
 
2.6%

Most occurring characters

ValueCountFrequency (%)
N21
27.6%
O11
14.5%
C10
13.2%
S9
11.8%
U7
 
9.2%
B5
 
6.6%
G4
 
5.3%
E3
 
3.9%
R2
 
2.6%
J1
 
1.3%
Other values (3)3
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter76
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N21
27.6%
O11
14.5%
C10
13.2%
S9
11.8%
U7
 
9.2%
B5
 
6.6%
G4
 
5.3%
E3
 
3.9%
R2
 
2.6%
J1
 
1.3%
Other values (3)3
 
3.9%

Most occurring scripts

ValueCountFrequency (%)
Latin76
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N21
27.6%
O11
14.5%
C10
13.2%
S9
11.8%
U7
 
9.2%
B5
 
6.6%
G4
 
5.3%
E3
 
3.9%
R2
 
2.6%
J1
 
1.3%
Other values (3)3
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII76
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N21
27.6%
O11
14.5%
C10
13.2%
S9
11.8%
U7
 
9.2%
B5
 
6.6%
G4
 
5.3%
E3
 
3.9%
R2
 
2.6%
J1
 
1.3%
Other values (3)3
 
3.9%

_embedded.show.webChannel.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct10
Distinct (%)26.3%
Missing22
Missing (%)36.7%
Memory size608.0 B
Europe/Oslo
11 
Asia/Shanghai
10 
America/New_York
Europe/London
Europe/Madrid
Other values (5)

Length

Max length16
Median length15
Mean length12.94736842
Min length10

Characters and Unicode

Total characters492
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)13.2%

Sample

1st rowAsia/Shanghai
2nd rowAsia/Shanghai
3rd rowAsia/Shanghai
4th rowAsia/Tokyo
5th rowAsia/Shanghai

Common Values

ValueCountFrequency (%)
Europe/Oslo11
18.3%
Asia/Shanghai10
16.7%
America/New_York6
 
10.0%
Europe/London4
 
6.7%
Europe/Madrid2
 
3.3%
Asia/Tokyo1
 
1.7%
Asia/Seoul1
 
1.7%
Australia/Sydney1
 
1.7%
Europe/Stockholm1
 
1.7%
America/Noronha1
 
1.7%
(Missing)22
36.7%

Length

2022-09-05T21:42:29.640854image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:42:29.757450image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
europe/oslo11
28.9%
asia/shanghai10
26.3%
america/new_york6
15.8%
europe/london4
 
10.5%
europe/madrid2
 
5.3%
asia/tokyo1
 
2.6%
asia/seoul1
 
2.6%
australia/sydney1
 
2.6%
europe/stockholm1
 
2.6%
america/noronha1
 
2.6%

Most occurring characters

ValueCountFrequency (%)
o50
 
10.2%
a44
 
8.9%
/38
 
7.7%
r35
 
7.1%
e33
 
6.7%
i32
 
6.5%
s24
 
4.9%
h22
 
4.5%
n20
 
4.1%
u20
 
4.1%
Other values (20)174
35.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter366
74.4%
Uppercase Letter82
 
16.7%
Other Punctuation38
 
7.7%
Connector Punctuation6
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o50
13.7%
a44
12.0%
r35
9.6%
e33
9.0%
i32
8.7%
s24
 
6.6%
h22
 
6.0%
n20
 
5.5%
u20
 
5.5%
p18
 
4.9%
Other values (9)68
18.6%
Uppercase Letter
ValueCountFrequency (%)
A20
24.4%
E18
22.0%
S13
15.9%
O11
13.4%
N7
 
8.5%
Y6
 
7.3%
L4
 
4.9%
M2
 
2.4%
T1
 
1.2%
Other Punctuation
ValueCountFrequency (%)
/38
100.0%
Connector Punctuation
ValueCountFrequency (%)
_6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin448
91.1%
Common44
 
8.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o50
 
11.2%
a44
 
9.8%
r35
 
7.8%
e33
 
7.4%
i32
 
7.1%
s24
 
5.4%
h22
 
4.9%
n20
 
4.5%
u20
 
4.5%
A20
 
4.5%
Other values (18)148
33.0%
Common
ValueCountFrequency (%)
/38
86.4%
_6
 
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII492
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o50
 
10.2%
a44
 
8.9%
/38
 
7.7%
r35
 
7.1%
e33
 
6.7%
i32
 
6.5%
s24
 
4.9%
h22
 
4.5%
n20
 
4.1%
u20
 
4.1%
Other values (20)174
35.4%

_embedded.show._links.nextepisode.href
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct5
Distinct (%)100.0%
Missing55
Missing (%)91.7%
Memory size608.0 B
https://api.tvmaze.com/episodes/2259041
https://api.tvmaze.com/episodes/2309443
https://api.tvmaze.com/episodes/2376729
https://api.tvmaze.com/episodes/2383512
https://api.tvmaze.com/episodes/2377389

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters195
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2259041
2nd rowhttps://api.tvmaze.com/episodes/2309443
3rd rowhttps://api.tvmaze.com/episodes/2376729
4th rowhttps://api.tvmaze.com/episodes/2383512
5th rowhttps://api.tvmaze.com/episodes/2377389

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/22590411
 
1.7%
https://api.tvmaze.com/episodes/23094431
 
1.7%
https://api.tvmaze.com/episodes/23767291
 
1.7%
https://api.tvmaze.com/episodes/23835121
 
1.7%
https://api.tvmaze.com/episodes/23773891
 
1.7%
(Missing)55
91.7%

Length

2022-09-05T21:42:29.847685image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:42:29.934367image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/22590411
20.0%
https://api.tvmaze.com/episodes/23094431
20.0%
https://api.tvmaze.com/episodes/23767291
20.0%
https://api.tvmaze.com/episodes/23835121
20.0%
https://api.tvmaze.com/episodes/23773891
20.0%

Most occurring characters

ValueCountFrequency (%)
/20
 
10.3%
p15
 
7.7%
s15
 
7.7%
e15
 
7.7%
t15
 
7.7%
o10
 
5.1%
a10
 
5.1%
i10
 
5.1%
.10
 
5.1%
m10
 
5.1%
Other values (16)65
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter125
64.1%
Other Punctuation35
 
17.9%
Decimal Number35
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p15
12.0%
s15
12.0%
e15
12.0%
t15
12.0%
o10
8.0%
a10
8.0%
i10
8.0%
m10
8.0%
h5
 
4.0%
d5
 
4.0%
Other values (3)15
12.0%
Decimal Number
ValueCountFrequency (%)
28
22.9%
37
20.0%
94
11.4%
74
11.4%
43
 
8.6%
52
 
5.7%
02
 
5.7%
12
 
5.7%
82
 
5.7%
61
 
2.9%
Other Punctuation
ValueCountFrequency (%)
/20
57.1%
.10
28.6%
:5
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin125
64.1%
Common70
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/20
28.6%
.10
14.3%
28
 
11.4%
37
 
10.0%
:5
 
7.1%
94
 
5.7%
74
 
5.7%
43
 
4.3%
52
 
2.9%
02
 
2.9%
Other values (3)5
 
7.1%
Latin
ValueCountFrequency (%)
p15
12.0%
s15
12.0%
e15
12.0%
t15
12.0%
o10
8.0%
a10
8.0%
i10
8.0%
m10
8.0%
h5
 
4.0%
d5
 
4.0%
Other values (3)15
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII195
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/20
 
10.3%
p15
 
7.7%
s15
 
7.7%
e15
 
7.7%
t15
 
7.7%
o10
 
5.1%
a10
 
5.1%
i10
 
5.1%
.10
 
5.1%
m10
 
5.1%
Other values (16)65
33.3%

_embedded.show.image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing60
Missing (%)100.0%
Memory size608.0 B

_embedded.show.dvdCountry.name
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing59
Missing (%)98.3%
Memory size608.0 B
Ukraine

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowUkraine

Common Values

ValueCountFrequency (%)
Ukraine1
 
1.7%
(Missing)59
98.3%

Length

2022-09-05T21:42:30.014509image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:42:30.087806image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
ukraine1
100.0%

Most occurring characters

ValueCountFrequency (%)
U1
14.3%
k1
14.3%
r1
14.3%
a1
14.3%
i1
14.3%
n1
14.3%
e1
14.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6
85.7%
Uppercase Letter1
 
14.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
k1
16.7%
r1
16.7%
a1
16.7%
i1
16.7%
n1
16.7%
e1
16.7%
Uppercase Letter
ValueCountFrequency (%)
U1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin7
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U1
14.3%
k1
14.3%
r1
14.3%
a1
14.3%
i1
14.3%
n1
14.3%
e1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII7
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U1
14.3%
k1
14.3%
r1
14.3%
a1
14.3%
i1
14.3%
n1
14.3%
e1
14.3%

_embedded.show.dvdCountry.code
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing59
Missing (%)98.3%
Memory size608.0 B
UA

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowUA

Common Values

ValueCountFrequency (%)
UA1
 
1.7%
(Missing)59
98.3%

Length

2022-09-05T21:42:30.153377image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:42:30.229417image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
ua1
100.0%

Most occurring characters

ValueCountFrequency (%)
U1
50.0%
A1
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter2
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U1
50.0%
A1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U1
50.0%
A1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U1
50.0%
A1
50.0%

_embedded.show.dvdCountry.timezone
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing59
Missing (%)98.3%
Memory size608.0 B
Europe/Zaporozhye

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters17
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowEurope/Zaporozhye

Common Values

ValueCountFrequency (%)
Europe/Zaporozhye1
 
1.7%
(Missing)59
98.3%

Length

2022-09-05T21:42:30.302950image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:42:30.386754image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
europe/zaporozhye1
100.0%

Most occurring characters

ValueCountFrequency (%)
o3
17.6%
r2
11.8%
p2
11.8%
e2
11.8%
E1
 
5.9%
u1
 
5.9%
/1
 
5.9%
Z1
 
5.9%
a1
 
5.9%
z1
 
5.9%
Other values (2)2
11.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter14
82.4%
Uppercase Letter2
 
11.8%
Other Punctuation1
 
5.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o3
21.4%
r2
14.3%
p2
14.3%
e2
14.3%
u1
 
7.1%
a1
 
7.1%
z1
 
7.1%
h1
 
7.1%
y1
 
7.1%
Uppercase Letter
ValueCountFrequency (%)
E1
50.0%
Z1
50.0%
Other Punctuation
ValueCountFrequency (%)
/1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin16
94.1%
Common1
 
5.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o3
18.8%
r2
12.5%
p2
12.5%
e2
12.5%
E1
 
6.2%
u1
 
6.2%
Z1
 
6.2%
a1
 
6.2%
z1
 
6.2%
h1
 
6.2%
Common
ValueCountFrequency (%)
/1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII17
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o3
17.6%
r2
11.8%
p2
11.8%
e2
11.8%
E1
 
5.9%
u1
 
5.9%
/1
 
5.9%
Z1
 
5.9%
a1
 
5.9%
z1
 
5.9%
Other values (2)2
11.8%

Interactions

2022-09-05T21:42:20.120252image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:09.694786image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:10.660574image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:11.545579image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:12.407909image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:13.279430image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:14.115444image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:14.981015image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:15.849172image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:16.720921image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:17.547834image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:18.365692image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:19.258885image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:20.186230image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:09.858657image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:10.730207image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:11.615761image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:12.478560image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:13.344727image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:14.185127image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:15.049767image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:15.916402image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:16.786613image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:17.615999image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:18.437725image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:19.326834image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:20.254173image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:09.928696image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:10.800285image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:11.685492image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:12.548472image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:13.412751image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:14.254996image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:15.120408image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:15.987143image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:16.853253image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:17.677972image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:18.510270image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:19.395615image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:20.318506image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:09.996705image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:10.869097image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:11.753389image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:12.611310image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:13.478258image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:14.317466image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:15.188577image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:16.054879image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:16.917870image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:17.738368image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:18.580756image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:19.463508image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:20.387781image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:10.064614image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:10.937433image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:11.818104image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:12.680118image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:13.543172image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:14.385554image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:15.257342image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:16.123782image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:16.982371image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:17.801478image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:18.647913image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:19.530573image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:20.447250image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
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2022-09-05T21:42:11.001988image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:11.881329image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:12.743971image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:13.603303image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:14.448177image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:15.320836image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:16.188104image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:17.042367image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:17.864420image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:18.712557image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:19.593595image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:20.516743image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:10.196330image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:11.071204image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:11.945804image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:12.812100image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:13.669134image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:14.515536image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:15.389507image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:16.255554image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:17.107663image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:17.927040image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:18.781656image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:19.661007image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:20.582338image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:10.264437image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:11.141210image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:12.014947image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:12.881544image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:13.735485image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:14.584140image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:15.458850image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:16.318681image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:17.172535image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:17.990369image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:18.851104image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:19.729097image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:20.651443image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:10.331640image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:11.210474image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:12.081458image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:12.950942image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:13.801033image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:14.651879image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:15.524040image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:16.389151image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:17.236106image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:18.053810image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:18.919230image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:19.794896image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:20.710484image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:10.395134image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:11.275114image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:12.145220image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:13.014051image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:13.860923image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:14.714330image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:15.586620image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:16.450396image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:17.295175image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:18.114099image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:18.984119image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:19.858252image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:20.768816image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:10.460522image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:11.338075image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:12.206485image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:13.076243image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
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2022-09-05T21:42:14.776778image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:15.649428image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:16.518338image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:17.357267image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:18.177669image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:19.051621image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:19.921828image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:20.835333image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:10.531036image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:11.411246image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:12.277724image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:13.144727image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:13.992629image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:14.846194image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:15.719166image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:16.586365image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:17.423993image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:18.244455image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:19.125615image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:19.991937image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:20.898278image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:10.596713image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:11.480499image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:12.344047image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:13.210974image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:14.055840image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:14.912174image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:15.785851image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:16.650814image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:17.487363image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:18.308045image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:19.194685image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:42:20.058307image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Correlations

2022-09-05T21:42:30.478897image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-09-05T21:42:30.715540image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-09-05T21:42:30.947790image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-09-05T21:42:31.223813image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-09-05T21:42:21.235455image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-09-05T21:42:21.895839image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-09-05T21:42:22.395399image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimesummaryrating.averageimage.mediumimage.original_links.self.href_embedded.show.id_embedded.show.url_embedded.show.name_embedded.show.type_embedded.show.language_embedded.show.genres_embedded.show.status_embedded.show.runtime_embedded.show.averageRuntime_embedded.show.premiered_embedded.show.ended_embedded.show.officialSite_embedded.show.schedule.time_embedded.show.schedule.days_embedded.show.rating.average_embedded.show.weight_embedded.show.network.id_embedded.show.network.name_embedded.show.network.country.name_embedded.show.network.country.code_embedded.show.network.country.timezone_embedded.show.network.officialSite_embedded.show.webChannel_embedded.show.dvdCountry_embedded.show.externals.tvrage_embedded.show.externals.thetvdb_embedded.show.externals.imdb_embedded.show.image.medium_embedded.show.image.original_embedded.show.summary_embedded.show.updated_embedded.show._links.self.href_embedded.show._links.previousepisode.hrefimage_embedded.show.network_embedded.show.webChannel.id_embedded.show.webChannel.name_embedded.show.webChannel.country_embedded.show.webChannel.officialSite_embedded.show.webChannel.country.name_embedded.show.webChannel.country.code_embedded.show.webChannel.country.timezone_embedded.show._links.nextepisode.href_embedded.show.image_embedded.show.dvdCountry.name_embedded.show.dvdCountry.code_embedded.show.dvdCountry.timezone
02121268https://www.tvmaze.com/episodes/2121268/fiksiki-4x17-internet-magazinИнтернет-магазин417.0regular2020-12-132020-12-13T00:00:00+00:006.0NoneNaNhttps://static.tvmaze.com/uploads/images/medium_landscape/353/883108.jpghttps://static.tvmaze.com/uploads/images/original_untouched/353/883108.jpghttps://api.tvmaze.com/episodes/212126838199https://www.tvmaze.com/shows/38199/fiksikiФиксикиAnimationRussian[]Running6.06.02010-12-13Nonehttp://www.fixiki.ru[Friday]NaN14239.0Россия 1Russian FederationRUAsia/KamchatkaNoneNaNNaNNone244021.0tt3886188https://static.tvmaze.com/uploads/images/medium_portrait/164/410098.jpghttps://static.tvmaze.com/uploads/images/original_untouched/164/410098.jpgNone1659704750https://api.tvmaze.com/shows/38199https://api.tvmaze.com/episodes/2370911NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
11985046https://www.tvmaze.com/episodes/1985046/a-seba-znau-1x12-12-vypusk-garik-harlamov12 выпуск – Гарик Харламов112.0regular2020-12-1312:002020-12-13T00:00:00+00:0090.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/198504647865https://www.tvmaze.com/shows/47865/a-seba-znauЯ СЕБЯ ЗНАЮ!Talk ShowRussian[Comedy]RunningNaN71.02020-05-01Nonehttps://premier.one/show/11906[Wednesday]NaN59NaNNaNNaNNaNNaNNaNNaNNaNNoneNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/255/639024.jpghttps://static.tvmaze.com/uploads/images/original_untouched/255/639024.jpgNone1655470164https://api.tvmaze.com/shows/47865https://api.tvmaze.com/episodes/2348600NaNNaN21.0YouTubeNaNhttps://www.youtube.comNaNNaNNaNNaNNaNNaNNaNNaN
21956339https://www.tvmaze.com/episodes/1956339/hero-return-1x10-episode-10Episode 10110.0regular2020-12-1310:002020-12-13T02:00:00+00:0015.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/195633951471https://www.tvmaze.com/shows/51471/hero-returnHero ReturnAnimationChinese[Action, Anime, Science-Fiction]Running15.016.02020-10-18Nonehttps://v.qq.com/detail/q/q72jd29a3oxflsr.html10:00[Sunday]NaN82NaNNaNNaNNaNNaNNaNNaNNaNNoneNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/279/698895.jpghttps://static.tvmaze.com/uploads/images/original_untouched/279/698895.jpg<p>Zero was mankind's first real superhero. Under his watch, countless other superheros appeared and followed in his footsteps. However, after 5 years of war, Zero disappeared without a trace.<br /><br />(Source: zeroscans)</p>1603467037https://api.tvmaze.com/shows/51471https://api.tvmaze.com/episodes/1956341NaNNaN104.0Tencent QQNaNhttps://v.qq.com/ChinaCNAsia/ShanghaiNaNNaNNaNNaNNaN
31985601https://www.tvmaze.com/episodes/1985601/swallowed-star-1x04-episode-4Episode 414.0regular2020-12-1310:002020-12-13T02:00:00+00:00NaNNoneNaNNaNNaNhttps://api.tvmaze.com/episodes/198560152178https://www.tvmaze.com/shows/52178/swallowed-starSwallowed StarAnimationChinese[Anime, Science-Fiction]RunningNaN21.02020-11-29Nonehttps://v.qq.com/detail/3/324olz7ilvo2j5f.html10:00[Wednesday]7.793NaNNaNNaNNaNNaNNaNNaNNaNNone392598.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/286/715165.jpghttps://static.tvmaze.com/uploads/images/original_untouched/286/715165.jpg<p>One day, an unexplained RR virus appeared on the earth, drawing the world into disaster. Infected animals mutated into terrible monsters, invaded massively, and humans built walls around the destruction and established the base city as the last bastion for humans. The suffering that mankind has experienced during this period of time is known as the "Great Nirvana Period." Not only that, Luo Feng not only carried the burden of supporting the family but also to protect the human homeland, for the better survival and development of mankind, together with other justice warriors, to join hands against the fierce monsters. Under the desperate situation of the end, can Luo Feng and other warriors repel monsters and successfully protect the human world?</p>1661959856https://api.tvmaze.com/shows/52178https://api.tvmaze.com/episodes/2259040NaNNaN104.0Tencent QQNaNhttps://v.qq.com/ChinaCNAsia/Shanghaihttps://api.tvmaze.com/episodes/2259041NaNNaNNaNNaN
42052508https://www.tvmaze.com/episodes/2052508/wu-shen-zhu-zai-1x83-episode-83Episode 83183.0regular2020-12-1310:002020-12-13T02:00:00+00:008.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/205250854033https://www.tvmaze.com/shows/54033/wu-shen-zhu-zaiWu Shen Zhu ZaiAnimationChinese[Action, Adventure, Anime, Fantasy]Running8.08.02020-03-08Nonehttps://v.qq.com/detail/m/7q544xyrava3vxf.html10:00[Tuesday, Sunday]NaN82NaNNaNNaNNaNNaNNaNNaNNaNNone379070.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/299/748854.jpghttps://static.tvmaze.com/uploads/images/original_untouched/299/748854.jpg<p>The protagonist Qin Chen, who was originally the top genius in the military domain, was conspired by the people to fall into the death canyon in the forbidden land of the mainland. Qin Chen, who was inevitably dead, unexpectedly triggered the power of the mysterious ancient sword.<br /><br />Three hundred years later, in a remote part of the Tianwu mainland, a boy of the same name accidentally inherited Qin Chen's will. As the beloved grandson of King Dingwu of the Daqi National Army, due to the birth father's birth, the mother and son were treated coldly in Dingwu's palace and lived together. In order to rewrite the myth of the strong man in hope of the sun, and to protect everything he loves, Qin Chen resolutely took up the responsibility of maintaining the five kingdoms of the world and set foot on the road of martial arts again.</p>1649423444https://api.tvmaze.com/shows/54033https://api.tvmaze.com/episodes/2309442NaNNaN104.0Tencent QQNaNhttps://v.qq.com/ChinaCNAsia/Shanghaihttps://api.tvmaze.com/episodes/2309443NaNNaNNaNNaN
51965924https://www.tvmaze.com/episodes/1965924/new-japan-pro-wrestling-2020-12-13-super-j-cup-2020Super J Cup 2020202087.0regular2020-12-1312:002020-12-13T03:00:00+00:00120.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/196592424963https://www.tvmaze.com/shows/24963/new-japan-pro-wrestlingNew Japan Pro WrestlingSportsJapanese[]Running120.098.02015-01-04Nonehttp://www.njpw1972.com/[Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday]NaN80NaNNaNNaNNaNNaNNaNNaNNaNNoneNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/96/240462.jpghttps://static.tvmaze.com/uploads/images/original_untouched/96/240462.jpg<p><b>New Japan Pro Wrestling</b> (NJPW) is the largest professional wrestling promotion in Japan and the second largest promotion in the world.</p>1661006042https://api.tvmaze.com/shows/24963https://api.tvmaze.com/episodes/2376728NaNNaN160.0NJPW WorldNaNNoneJapanJPAsia/Tokyohttps://api.tvmaze.com/episodes/2376729NaNNaNNaNNaN
62012321https://www.tvmaze.com/episodes/2012321/mans-diary-2x06-episode-6Episode 626.0regular2020-12-132020-12-13T04:00:00+00:0012.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/201232150398https://www.tvmaze.com/shows/50398/mans-diaryMan's DiaryAnimationChinese[Anime, Supernatural]Running12.012.02019-07-21Nonehttps://www.bilibili.com/bangumi/media/md4314622[Sunday]NaN4NaNNaNNaNNaNNaNNaNNaNNaNNone379528.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/273/683332.jpghttps://static.tvmaze.com/uploads/images/original_untouched/273/683332.jpg<p>In the twenty-first century, gods and demons can no longer maintain balance due to the rapid development of human society. In an effort to restore proper order, the gods began to take care of saving the world, for which they sent a group of gods and monsters to the world of people, who must find there the " key " to salvation. Su moting is a girl with the personality of "demon child". When her parents asked her to leave home so that she could become independent and independent, she met the beautiful and charming God of Tianjin and the mysterious demon cat. So begins a new turbulent round of su moting's life.</p><p><br /> </p>1611039497https://api.tvmaze.com/shows/50398https://api.tvmaze.com/episodes/2012327NaNNaN51.0BilibiliNaNNoneChinaCNAsia/ShanghaiNaNNaNNaNNaNNaN
72071471https://www.tvmaze.com/episodes/2071471/youths-in-the-breeze-1x01-the-boy-and-the-cat-01THE BOY AND THE CAT #0111.0regular2020-12-132020-12-13T04:00:00+00:007.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/207147154762https://www.tvmaze.com/shows/54762/youths-in-the-breezeYouths in the BreezeScriptedChinese[Drama, Fantasy]Ended7.07.02020-12-132020-12-22https://v.youku.com/v_show/id_XNDk4OTUxMzg1Mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef[Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday]NaN27NaNNaNNaNNaNNaNNaNNaNNaNNone397247.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/308/770106.jpghttps://static.tvmaze.com/uploads/images/original_untouched/308/770106.jpg<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>1618466682https://api.tvmaze.com/shows/54762https://api.tvmaze.com/episodes/2071494NaNNaN118.0YoukuNaNNoneChinaCNAsia/ShanghaiNaNNaNNaNNaNNaN
82071472https://www.tvmaze.com/episodes/2071472/youths-in-the-breeze-1x02-the-boy-and-the-cat-02THE BOY AND THE CAT #0212.0regular2020-12-132020-12-13T04:00:00+00:007.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/207147254762https://www.tvmaze.com/shows/54762/youths-in-the-breezeYouths in the BreezeScriptedChinese[Drama, Fantasy]Ended7.07.02020-12-132020-12-22https://v.youku.com/v_show/id_XNDk4OTUxMzg1Mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef[Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday]NaN27NaNNaNNaNNaNNaNNaNNaNNaNNone397247.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/308/770106.jpghttps://static.tvmaze.com/uploads/images/original_untouched/308/770106.jpg<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>1618466682https://api.tvmaze.com/shows/54762https://api.tvmaze.com/episodes/2071494NaNNaN118.0YoukuNaNNoneChinaCNAsia/ShanghaiNaNNaNNaNNaNNaN
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531985914https://www.tvmaze.com/episodes/1985914/idolish7-2x13-lies-and-formalityLies and Formality213.0regular2020-12-132020-12-13T17:00:00+00:0025.0<p>Filming for the drama Tamaki and Sogo are co-starring in is going well. However, Sogo continues to worry about his encounter with Tamaki's younger sister, which he hasn't been able to tell anyone about. On the final day of the special unit's joint practice, Tamaki is shocked to discover that Sogo couldn't trust him emough to tell him about Aya.</p>NaNNaNNaNhttps://api.tvmaze.com/episodes/198591433463https://www.tvmaze.com/shows/33463/idolish7IDOLiSH7AnimationJapanese[Anime, Music]Running25.025.02017-11-02Nonehttp://idolish7.com/aninana/22:30[Sunday]NaN68132.0Tokyo MXJapanJPAsia/TokyoNoneNaNNaNNone337336.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/295/737516.jpghttps://static.tvmaze.com/uploads/images/original_untouched/295/737516.jpg<p>A group of aspiring idols gather at Takanashi Productions and are entrusted with the company's future. The seven men who have just met represent a variety of totally different personalities. However, they each have their own charm and possess unknown potential as idols. Forming a group, they take their first step together as <b>IDOLiSH7</b>. Their brilliantly shining dancing forms onstage eventually begin captivating the hearts of the people. In the glorious but sometimes harsh world of idols, they aim for the top with dreams in their hearts!</p>1628688100https://api.tvmaze.com/shows/33463https://api.tvmaze.com/episodes/2146076NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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582234689https://www.tvmaze.com/episodes/2234689/one-mo-chance-1x09-new-york-new-yorkNew York, New York19.0regular2020-12-1320:002020-12-14T01:00:00+00:0046.0<p>On a journey to find love, Chance invites 15 beautiful "ladies" into his home. Each week he will put the hopefuls through various challenges to test their compatibility among other things. However, with constant infighting between the contestants, will Chance be able to finally find his happily ever after?</p>NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/382/955840.jpghttps://static.tvmaze.com/uploads/images/original_untouched/382/955840.jpghttps://api.tvmaze.com/episodes/223468959398https://www.tvmaze.com/shows/59398/one-mo-chanceOne Mo' ChanceRealityEnglish[]RunningNaN47.02020-10-11Nonehttps://www.thezeusnetwork.com/one-mo-chance20:00[Sunday]NaN56NaNNaNNaNNaNNaNNaNNaNNaNNone390130.0tt14369906https://static.tvmaze.com/uploads/images/medium_portrait/382/955908.jpghttps://static.tvmaze.com/uploads/images/original_untouched/382/955908.jpg<p>From the breakdown of his relationship with the mother of his children, to the death of his brother and partner Real," the last few years have been personally tough for Kamal Chance Givens. However, the original Stallionaire is now ready to get back on his horse to give love another shot. During Chance return to reality television we'll watch as he goes it alone to find the true love of his life in this new dating competition series.</p>1649330631https://api.tvmaze.com/shows/59398https://api.tvmaze.com/episodes/2308893NaNNaN331.0ZeusNaNNoneUnited StatesUSAmerica/New_YorkNaNNaNNaNNaNNaN
592274707https://www.tvmaze.com/episodes/2274707/couples-therapy-1x10-the-covid-specialThe COVID Special110.0regular2020-12-1322:002020-12-14T03:00:00+00:0060.0<p>Dr. Guralnik and her patients struggle with the realities of Covid-19.</p>NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/411/1029480.jpghttps://static.tvmaze.com/uploads/images/original_untouched/411/1029480.jpghttps://api.tvmaze.com/episodes/227470743299https://www.tvmaze.com/shows/43299/couples-therapyCouples TherapyDocumentaryEnglish[]Running30.031.02019-09-06Nonehttps://www.sho.com/couples-therapy[]6.591NaNNaNNaNNaNNaNNaNNaNNaNNone367813.0tt10665386https://static.tvmaze.com/uploads/images/medium_portrait/411/1029500.jpghttps://static.tvmaze.com/uploads/images/original_untouched/411/1029500.jpg<p><b>Couples Therapy</b> unlocks a hidden world: other people's relationships. Far from reality-show caricatures, this is true documentary filmmaking that brings viewers into the authentic and visceral experience of weekly therapy with four couples. World-class therapist Dr. Orna Guralnik deftly guides the couples through the minefield of honest confrontation with each other and with themselves, revealing the real-life struggles - and extraordinary breakthroughs - typically hidden behind closed doors.</p>1654441117https://api.tvmaze.com/shows/43299https://api.tvmaze.com/episodes/2339862NaNNaN315.0Showtime on DemandNaNNoneUnited StatesUSAmerica/New_YorkNaNNaNNaNNaNNaN